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Helicases are involved in almost every nucleic acid metabolism process. Within this family, RecQ helicase proteins protect genome integrity across all organisms through DNA recombination, repair, and replication. This study focused on five Arabidopsis thaliana RecQ-like (AtRecQl) genes with diverse functionalities. Analysis of ProAtRecQl: GUS expression during vegetative and reproductive development stages revealed organ- and tissue-specific patterns. Changes in AtRecQls transcript levels in response to abiotic stressors suggest their involvement in diverse stimuli responses. Notably, germination and growth rates were lower in atrecql2 and atrecql3 mutants under various salt concentrations and cold conditions. These findings indicate that AtRecQl2 and AtRecQl3 act as positive regulators of abiotic stress tolerance during the germinative and postgerminative phases., (© The Author(s) 2024. Published by Oxford University Press on behalf of Japan Society for Bioscience, Biotechnology, and Agrochemistry.)

Deep learning and artificial intelligence offer promising tools for improving the accuracy and efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This study explores this potential by leveraging a large dataset containing over 6,000 CXR images from publicly available sources. These images encompass COVID-19 cases, normal cases, and patients with viral or bacterial pneumonia. The research proposes a novel approach called "Enhancing COVID Prediction with ESN-MDFS" that utilizes a combination of an Extreme Smart Network (ESN) and a Mean Dropout Feature Selection Technique (MDFS). This study aimed to enhance multi-class lung condition detection in portable chest X-rays by combining static texture features with dynamic deep learning features extracted from a pre-trained VGG-16 model. To optimize performance, preprocessing, data imbalance, and hyperparameter tuning were meticulously addressed. The proposed ESN-MDFS model achieved a peak accuracy of 96.18% with an AUC of 1.00 in a six-fold cross-validation. Our findings demonstrate the model's superior ability to differentiate between COVID-19, bacterial pneumonia, viral pneumonia, and normal conditions, promising significant advancements in diagnostic accuracy and efficiency., Competing Interests: The authors have declared that no competing interests exist, (Copyright: © 2024 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Alzheimer's disease (AD) is the leading form of dementia in the United States and the world. The pathophysiology of AD is complex and multifaceted. Accumulation of senile plaques and neurofibrillary tangles (NFTs) are hallmarks of AD. The aggregation of amyloid β (senile plaques) and tau tangles (NFTs) results in the death of neurons in the cortex and hippocampus, which manifests itself in cognitive decline and memory loss. Current therapies rely on conventional approaches that have only treated the underlying symptoms without disease modification. Data from clinical studies point to a complex role of amyloid β (Aβ) in a way that enhances the tau phenotype throughout the disease process. To address the co-pathogenic role of Aβ and tau, we undertook development of multitarget compounds aiming at both tau and Aβ to slow or stop disease progression and provide neuroprotection. Here, we demonstrate a dose-dependent effect of the novel test compounds that inhibit aggregation of AcPHF6 (a shorter version of tau protein) and Aβ 1-42 peptides in thioflavin T fluorescent assays. The compounds were also shown to disaggregate preformed aggregates dose dependently. To further validate these findings, circular dichroism experiments were carried out to examine the nature of inhibition. Additionally, transmission electron microscopy experiments were carried out to gain insights into the morphologies of aggregates obtained from dose-dependent inhibition of AcPHF6 and Aβ 1-42 as well as dissociation of preformed aggregates from these peptides. Compounds D-687 and D-688 reversed Aβ 1-42 induced toxicity in SH-SH5Y cells, significantly demonstrating neuroprotective properties. Finally, in a study with Drosophila melanogaster expressing human tau protein isoform (2N4R) in all the neurons, compound D-688 significantly increased the survival of flies compared to vehicle treated controls. Future studies will further examine the neuroprotective properties of these lead compounds in various animal models.

Background: Familial hypercholesterolemia (FH) is a frequently underdiagnosed genetic disorder characterized by elevated low-density lipoprotein (LDL) levels. Genetic testing of LDLR, APOB, and PCSK9 genes can identify variants in up to 80% of clinically diagnosed patients. However, limitations in time, scalability, and cost have hindered effective next-generation sequencing of these genes. Additionally, pharmacogenomic variants are associated with statin-induced adverse effects in FH patients. To address these challenges, we developed a multiplex primer-based amplicon sequencing approach for FH genetic testing., Methods: Multiplex primers were designed for the exons of the LDLR, APOB, and PCSK9 genes, as well as for pharmacogenomic variants rs4149056 (SLCO1B1:c.521T > A), rs2306283 (SLCO1B1:c.388A > G), and rs2231142 (ABCG2:c.421C > A). Analytical validation using samples with known pathogenic variants and clinical validation with 12 FH-suspected probands were conducted. Library preparation was based on a bead-based tagmentation method, and sequencing was conducted on the NovaSeq 6000 platform., Results: Our approach ensured no amplicon dropouts, with over 100× coverage on each amplicon. Known variants in 2 samples were successfully detected. Further, we identified one heterozygous LDLR (p.Glu228Ter) variant and 2 homozygous cases of LDLR (p.Lys294Ter) and LDLR (p.Ser177Leu) variants in patients. Pharmacogenomic analysis revealed that overall 3 patients may require reduced statin doses. Our approach offered reduced library preparation time (approximately 3 h), greater scalability, and lower costs (under $50) for FH genetic testing., Conclusions: Our method effectively sequences LDLR, APOB, and PCSK9 genes including pharmacogenomic variants that will guide appropriate screening and statin dosing, thus increasing both efficiency and affordability., (© Association for Diagnostics & Laboratory Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: The pathophysiology of Acute Pancreatitis (AP) may be complicated by endothelial activation. von Willebrand Factor (vWF)- ADAMTS13 axis is a marker of endothelial activation. The study aimed to investigate the axis in AP, comparing it in patients with and without persistent organ failure (OF), with and without pancreatic necrosis, and correlating it with the standard severity scores (CRP, APACHE II, BISAP, SOFA, and qSOFA) METHODS: vWF-Antigen (vWF:Ag), vWF-Collagen-Binding-Assay (vWF:CBA), and ADAMTS13 activity (ADAMTS13:act) levels were measured within 5 days of symptom onset in consecutive patients (n = 98), who were admitted with a first episode of AP (Dec 2021-May 2023)., Results: Of the 98 patients admitted with AP, 78(79.6 %) had no or transient OF; 20(20.4 %) had persistent OF. Age was comparable (43.73 ± 15.36 vs 38.65 ± 13.69) [mean ± SD](years), and males were predominant in both groups (70.5 % vs 80 %). Patientswith persistent OF had higher vWF:CBA(%)[323(279-486.5) vs 199.5(159.1-295.75)] and lower ADAMTS13:act(%)[35.4(23.8-56.85) vs 56.35(44.1-71.9)][median (25th - 75th percentile)](P = 0.001) than those with no or transient OF. Patients with pancreatic necrosis (n = 19) had lower ADAMTS13:act(%)[42.79 ± 18.69] than those without pancreatic necrosis (n = 18) [62.49 ± 22.64] (P < 0.01). ADAMTS13:act had a negative correlation(r = -0.2), whereas vWF:Ag and vWF:CBA had a positive correlation (r = 0.2) with the standard severity scores (P < 0.05). ADAMTS13:act could predict pancreatic necrosis [AUROC-0.737, P < 0.05] and persistent OF [AUROC-0.746, P < 0.001], while vWF:CBA could predict persistent OF [AUROC- 0.73, P < 0.001]., Conclusion: vWF-ADAMTS13 axis helps to predict severe disease and is associated with poor outcomes in acute pancreatitis., (Copyright © 2024 IAP and EPC. Published by Elsevier B.V. All rights reserved.)

Purpose: The purpose of this study was to present the results of olecranon tendo-osseous allograft (OTOA) reconstruction for patients with an irreparable extensor mechanism from prior trauma or failed total elbow arthroplasty (TEA)., Methods: A retrospective review was performed of all patients with extensor mechanism loss after trauma or failed TEA who were treated with an OTOA to supplement fracture fixation or elbow arthroplasty, as indicated. Primary outcome measures were successful healing of the allograft, restoration of the extensor mechanism function, and Mayo Elbow Performance Scores (MEPS) at the most recent follow-up. Secondary outcomes included patients' active range of motion and unplanned operative interventions., Results: Nine patients had extensor mechanism and proximal ulna loss as a result of prior TEA, acute trauma, or failed surgeries for prior trauma. All but one had undergone multiple prior surgeries. The mean follow-up was 27 months (6-60 months). At the final follow-up, patients reported MEPS of 92 (80-100). All patients regained active triceps extension (strength 3-5/5). Mean final range of motion was 16° (0° to 45°) extension, 124° (70° to 150°) flexion, 56° (45° to 80°) pronation, and 60° (40° to 80°) supination. Eight (89%) of the nine patients had a radiographically healed graft at the latest follow-up, of which four healed without notable complications or further surgical intervention. Complications included radial/ulnar nerve palsy, allograft olecranon stress fracture, deep infection, wound complications, instability, and complications related to the TEA prosthesis., Conclusions: In the setting of elbow reconstruction in which there is inadequate triceps tendon and/or olecranon bone stock to perform internal fixation and/or revision arthroplasty, OTOA may supplement elbow reconstruction, albeit with high rates of complications. A triceps-olecranon allograft, combined with either internal fixation or TEA, is a potentially useful salvage procedure for managing bone loss and an irreparable extensor mechanism deficit at the elbow., Type of Study/level of Evidence: Therapeutic V., (Copyright © 2024 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Declaration of competing interest The authors have no conflicts of interest relevant to this article.

Aims: This study aims to describe a new method that may be used as a supplement to evaluate humeral rotational alignment during intramedullary nail (IMN) insertion using the profile of the perpendicular peak of the greater tuberosity and its relation to the transepicondylar axis. We called this angle the greater tuberosity version angle (GTVA)., Methods: This study analyzed 506 cadaveric humeri of adult patients. All humeri were CT scanned using 0.625 × 0.625 × 0.625 mm cubic voxels. The images acquired were used to generate 3D surface models of the humerus. Next, 3D landmarks were automatically calculated on each 3D bone using custom-written C++ software. The anatomical landmarks analyzed were the transepicondylar axis, the humerus anatomical axis, and the peak of the perpendicular axis of the greater tuberosity. Lastly, the angle between the transepicondylar axis and the greater tuberosity axis was calculated and defined as the GTVA., Results: The value of GTVA was 20.9° (SD 4.7°) (95% CI 20.47° to 21.3°). Results of analysis of variance revealed that females had a statistically significant larger angle of 21.95° (SD 4.49°) compared to males, which were found to be 20.49° (SD 4.8°) (p = 0.001)., Conclusion: This study identified a consistent relationship between palpable anatomical landmarks, enhancing IMN accuracy by utilizing 3D CT scans and replicating a 20.9° angle from the greater tuberosity to the transepicondylar axis. Using this angle as a secondary reference may help mitigate the complications associated with malrotation of the humerus following IMN. However, future trials are needed for clinical validation., Competing Interests: The authors have no conflicts of interest to disclose., (© 2024 Gutierrez-Naranjo et al.)

We describe the family of a patient with developmental delay, macrocephaly, dysmorphic facial features and autism. His mother also shared similar facial features and macrocephaly but not his neurobehavioural issues. Subsequently, both the child and his mother were found to have a heterozygous frameshift variant NFIX: c.34&#95;41dupGGGATACC. The child and his mother had many features consistent with a genetic diagnosis of Malan syndrome. Therefore, this family highlighted the variable expressivity of Malan syndrome., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Pharmacogenomic (PGx) factors significantly influence how patients respond to antipsychotic medications This systematic review was performed to synthesize the clinical utility of PGx-assisted treatment versus standard of care in schizophrenia., Methods: PubMed, Embase, and Cochrane CENTRAL databases were searched for randomized controlled trials (RCTs) from inception till June 2024 that had compared the clinical utility of PGx-assisted intervention as compared to the standard of care in schizophrenia. The primary outcome was safety, and the secondary outcomes were efficacy and medication adherence. Pooled standardized mean differences (SMD) along with a 95% confidence interval (CI) were calculated (random-effects model) wherever feasible., Results: A total of 18,821 studies were screened, and five were included for review. All the RCTs had a high risk of bias. Four studies included the commonly used antipsychotics. Three studies reported negative outcomes (safety, efficacy, and medication adherence) and two reported positive outcomes (safety) using different scales. In the meta-analysis, there were significant differences in the total Udvalg for Kliniske Undersogelser Side-Effect Rating scale score [SMD 0.95 (95% CI: 0.76-1.13), p < 0.001); I 2  = 0%] and the total Positive and Negative Syndrome Scale score [SMD 10.65 (95% CI: 2.37-18.93), p = 0.01); I 2  = 100%] between the PGx-assisted treatment and standard of care arms. However, the results were inconsistent, and the certainty of evidence (GRADE criteria) was very low., Conclusion: Current evidence on the clinical utility of PGx-assisted treatment in schizophrenia is limited and inconsistent and further evidence is required in this regard., (© 2024. The Author(s).)

One kind of autonomous vehicle that can take instructions from the driver by reading their electroencephalogram (EEG) signals using a Brain-Computer Interface (BCI) is called a Brain-Controlled Vehicle (BCV). The operation of such a vehicle is greatly affected by how well the BCI works. At present, there are limitations on the accuracy of BCI recognition, the number of distinguishable command categories, and the execution duration of command recognition. Consequently, vehicles that are exclusively controlled by EEG signals demonstrate suboptimal control performance. To address the difficulty of improving the control capabilities of brain-controlled cars while maintaining BCI performance, a fuzzy logic-based technique called as Fuzzy Brain-Control Fusion Control is introduced. This approach uses Fuzzy Discrete Event System (FDES) supervisory theory to verify the accuracy of the driver's brain-controlled directives. Concurrently, a fuzzy logic-based automatic controller is developed to generate decisions automatically in accordance with the present state of the vehicle via fuzzy reasoning. The final decision is then reached through the application of secondary fuzzy reasoning to the accuracy of the driver's instructions and the automated decisions to make adjustments that are more consistent with human intent. A clever BCI gadget known as the Consistent State Visual Evoked Potential (SSVEP) is utilized to show the viability of the proposed technique. We recommend that additional research should be conducted at this time to confirm that our recommended system may further improve the control execution of BCI-fueled cars, regardless of whether BCIs have special limitations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

ALS (Amyotrophic Lateral Sclerosis) is a neurodegenerative disorder causing profound physical disability that severely impairs a patient's life expectancy and quality of life. It also leads to muscular atrophy and progressive weakness of muscles due to insufficient nutrition in the body. At present, there are no disease-modifying therapies to cure ALS, and there is a lack of preventive tools. The general clinical assessments are based on symptom reports, neurophysiological tests, neurological examinations, and neuroimaging. But, these techniques possess various limitations of low reliability, lack of standardized protocols, and lack of sensitivity, especially in the early stages of disease. So, effective methods are required to detect the progression of the disease and minimize the suffering of patients. Extensive studies concentrated on investigating the causes of neurological disease, which creates a barrier to precise identification and classification of genes accompanied with ALS disease. Hence, the proposed system implements a deep RSFFNNCNN (Resemble Single Feed Forward Neural Network-Convolutional Neural Network) algorithm to effectively classify the clinical associations of ALS. It involves the addition of custom weights to the kernel initializer and neutralizer 'k' parameter to each hidden layer in the network. This is done to increase the stability and learning ability of the classifier. Additionally, the comparison of the proposed approach is performed with SFNN (Single Feed NN) and ML (Machine Learning) based algorithms, namely, NB (Naïve Bayes), XGBoost (Extreme Gradient Boosting) and RF (Random Forest), to estimate the efficacy of the proposed model. The reliability of the proposed algorithm is measured by deploying performance metrics such as precision, recall, F1 score, and accuracy., Competing Interests: Declaration of competing interest I am Abdullah Alqahtani Hereby state that the Manuscript title entitled “Intellectual Assessment of Amyotrophic Lateral Sclerosis Using Deep Resemble Forward Neural Network” Submitted to your Journal, I Confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. And I am Department of Software Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, KSA. I'm author of the paper. There is no other third party people are involved in this paper. The Author read and accept the paper to submit., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The structure and function of dietary proteins, as well as their subcellular prediction, are critical for designing and developing new drug compositions and understanding the pathophysiology of certain diseases. As a remedy, we provide a subcellular localization method based on feature fusion and clustering for dietary proteins. Additionally, an enhanced PseAAC (Pseudo-amino acid composition) method is suggested, which builds upon the conventional PseAAC. The study initially builds a novel model of representing the food protein sequence by integrating autocorrelation, chi density, and improved PseAAC to better convey information about the food protein sequence. After that, the dimensionality of the fused feature vectors is reduced by using principal component analysis. With prediction accuracies of 99.24% in the Gram-positive dataset and 95.33% in the Gram-negative dataset, respectively, the experimental findings demonstrate the practicability and efficacy of the proposed approach. This paper is basically exploring pseudo-amino acid composition of not any clinical aspect but exploring a pharmaceutical aspect for drug repositioning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: This study aimed to determine the effect of stepstool use on chest compression (CC) quality during cardiopulmonary resuscitation (CPR) in young children., Methods: We conducted a prospective observational study of children <8 years of age who received CC for >2 minutes in the emergency department. Data were collected through CC monitor device and video review. Data were analyzed in "CC segments" (periods of CC by individual providers). CC segments were coded "yes" or "no" for stepstool use based on video review. Univariate analyses of CC rate and depth between stepstool use and hand positions were performed through nonparametric testing, stratified by age category., Results: Forty-two patients received 566 minutes of CC. Overall, American Heart Association (AHA)-compliant (rate and depth) CPR was achieved in 10% of CC segments for children <1 year and only 6% in children >1 year. A stepstool was used in 73% of CC segments in children <1 year and 88% in children >1 year. In children >1 year, stepstool use was associated with deeper CCs (P < 0.001) and a more compliant CC rate (P < 0.01). In children >1 year, 7% of those with a stepstool in use achieved AHA compliance, compared to those without a stepstool, where none achieved AHA compliance., Conclusions: In children >1 year, stepstool use resulted in greater CC depth and more AHA-compliant CC rate. No CC segments in children >1 year achieved AHA compliance without a stepstool. These data support uniform stepstool use during pediatric CPR in children >1 year of age., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Fenugreek ( Trigonella foenum-graecum ) is a widely grown dietary herb in Asia, and its seeds are traditionally used for several diseases, including diabetes. The seeds and leaves possess a variety of compounds that play an important role in regulating their hypoglycemic effect. However, so far, no extensive systematic review exists on its antidiabetic effect, highlighting the molecular mechanisms and isolated compounds. The purpose of this review is to summarize the preclinical and clinical antidiabetic properties of fenugreek and its isolated compounds by focusing on underlying mechanisms. PubMed, Google Scholar, Science Direct, and Scopus databases were searched to retrieve articles until June, 2024. Preclinical studies demonstrated that the antidiabetic effect of fenugreek was mostly associated with enhanced glucose transporter type-4 (GLUT4) translocation and hexokinase activity, decreased glucose-6-phosphatase and fructose-1,6-bisphosphatase activities, inhibited α-amylase and maltase activities, protected β cells, and increased insulin release. Furthermore, few studies have reported its role as a glucagon-like peptide-1 (GLP-1) modulator, 5'-AMP-activated kinase (AMPK) activator, and dipeptidyl peptidase-IV (DPP-IV) inhibitor. Further clinical trials showed that fenugreek seeds improved blood glucose levels, insulin resistance, insulin sensitivity, and lipid profiles. This study highlights significant evidence of the antidiabetic effect of fenugreek and its isolated compounds; therefore, it could be a potential therapy for diabetes., Competing Interests: The authors declare no conflict of interest regarding this paper., (© 2024 The Author(s). Food Science & Nutrition published by Wiley Periodicals LLC.)

Background: Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Interfaces inspired deep learning-assisted diagnosis based on physiological signals holds promise for improving traditional methods lacking physiological basis and leads next generation neuro-technologies. However, traditional deep learning methods rely on immense computational power and mostly involve end-to-end network learning. These learning methods also lack physiological interpretability, limiting their clinical application in assisted diagnosis., Methodology: A brain-like learning model for diagnosing depression using electroencephalogram (EEG) is proposed. The study collects EEG data using 128-channel electrodes, producing a 128×128 brain adjacency matrix. Given the assumption of undirected connectivity, the upper half of the 128×128 matrix is chosen in order to minimise the input parameter size, producing 8,128-dimensional data. After eliminating 28 components derived from irrelevant or reference electrodes, a 90×90 matrix is produced, which can be used as an input for a single-channel brain-computer interface image., Result: At the functional level, a spiking neural network is constructed to classify individuals with depression and healthy individuals, achieving an accuracy exceeding 97.5 %., Comparison With Existing Methods: Compared to deep convolutional methods, the spiking method reduces energy consumption., Conclusion: At the structural level, complex networks are utilized to establish spatial topology of brain connections and analyse their graph features, identifying potential abnormal brain functional connections in individuals with depression., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To study the prevalence of synchronous oesophageal cancer in patients with head and neck cancers using Narrow Band Imaging and Lugol's chromoendoscopy., Materials and Methods: Study design: Prospective cross sectional diagnostic study. Method: 63 recruited patients with head and neck cancers, underwent haematologic evaluation, histological confirmation, imaging which included contrast enhanced computerised tomography(CECT) of the Neck and when indicated an additional Magnetic Resonance Imaging(MRI) scan followed by UGI endoscopy using white light followed by Narrow Band Imaging(NBI) and Lugol's chromoendoscopy(LCE)., Results: Oesophageal examination picked up a gastric inlet patch in 5 subjects and epithelial hyperplasia in one while the remaining 57 were normal on using White Light Endoscopy (WLE). NBI identified an abnormal pattern in 4 patients in whom WLE was normal (3 - Type II Intra Papillary Capillary Loop (IPCL) pattern, 1- Type III IPCL pattern). LCE showed unstained mucosa of < 10 mm in six patients, the histopathology reported were normal tissue in two patients, mild chronic oesophagitis in two and, gastric metaplasia and high grade dysplasia in one each respectively. Unstained mucosa of > 10 mm in one subject showed epithelial hyperplasia. Two patients had an abnormal NBI and LCE pattern although the WLE were normal., Conclusion: By utilizing NBI and LCE, although oesophageal cancer was not detected, premalignant pathology like high grade dysplasia, as well as gastric metaplasia, epithelial hyperplasia, esophagitis were detected. Using both NBI and LCE along with WLE would be complimentary to detect early pathological lesions. Capturing the lesions in the window period that exists between the transformation of epithelial dysplasia to carcinoma and treating them early will reduce the morbidity and also improve the outcome in oesophageal malignancy., Competing Interests: Competing InterestsThe authors declare that they have no conflict of interest., (© Association of Otolaryngologists of India 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Studies of longevity rely on baseline life expectancy of reference genotypes measured in standardized conditions. Variation among labs, protocols, and genotypes makes longevity intervention studies difficult to compare. Furthermore, extending lifespan under suboptimal conditions or that of a short-lived genotype may be of a lesser theoretical and translational value than extending the maximal possible lifespan. Daphnia is becoming a model organism of choice for longevity research complementing data obtained on traditional models. In this study, we report longevity of several genotypes of a long-lived species D. magna under a variety of protocols, aiming to document the highest lifespan, factors reducing it, and parameters that change with age and correlate with longevity. Combining longevity data from 25 experiments across two labs, we report a strong intraspecific variation, moderate effects of group size and medium composition, and strong genotype-by-environment interactions with respect to food level. Specifically, short-lived genotypes show no caloric restriction (CR) effect, while long-lived ones expand their lifespan even further under CR. We find that the CR non-responsive clones show little correlation between longevity and two measures of lipid peroxidation. In contrast, the long-lived, CR-responsive clones show a positive correlation between longevity and lipid hydroperoxide abundance, and a negative correlation with MDA concentration. This indicates differences among genotypes in age-related accumulation and detoxification of LPO products and their effects on longevity. Our observations support the hypothesis that a long lifespan can be affected by CR and levels of oxidative damage, while genetically determined short lifespan remains short regardless., (© 2024. The Author(s), under exclusive licence to American Aging Association.)

We have implemented a reduced-cost partial triples correction scheme to the equation of motion coupled cluster method for core-ionization energy based on state-specific natural orbitals. The second-order Algebraic Diagrammatic Construction (ADC) method is used to generate the state-specific natural orbital, which provides quicker convergence of the core-IP value with respect to the size of the virtual space than that observed in standard MP2-based natural orbitals. The error due to truncation of the virtual orbital can be reduced by using a perturbative correction. The accuracy of the method can be controlled by a single threshold, and there is a black box to use. The inclusion of the partial triples correction in the natural orbital based EOM-CCSD method greatly improves the agreement of the results with the experiment. The efficiency of the present implementation is demonstrated by calculating the core-ionization energy of a molecule containing 60 atoms and more than 2000 basis functions.

In the face of an aging population, smart healthcare services are now within reach, thanks to the proliferation of high-speed internet and other forms of digital technology. Data problems in smart healthcare, unfortunately, put artificial intelligence in this area to serious limitations. There are several issues, including a lack of standard samples, noisy data interference, and actual data that is missing. A three-stage AI-based data generating strategy is suggested to handle missing datasets, using a small sample dataset obtained from a smart healthcare program community in a specific city: Step one involves generating the dataset's basic attributes using a tree-based generation strategy that takes the original data distribution into account. Step two involves using the Naive Bayes algorithm to create basic indicators of behavioural capability assessment for the samples. Step three builds on stage two and uses a multivariate linear regression method to create evaluation criteria and indicators of high-level behavioural capability. Six problems involving multiple classifications and two tasks using multiple labels are implemented using various neural network-based training strategies on the obtained data to assess the usefulness of the dataset for downstream tasks. To ensure that the data collected is genuine and useful, the experimental data must be analysed and expert knowledge must be included., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Most classification models for Alzheimer's Diagnosis (AD) do not have specific strategies for individual input samples, leading to the problem of easily overlooking personalized differences between samples. This research introduces a customized dynamically ensemble convolution neural network (PDECNN), which is able to build a specific integration strategy based on the distinctiveness of the sample. In this paper, we propose a personalized dynamic ensemble alzheimer's Diagnosis classification model. This model will dynamically modify the deteriorated brain areas of interest depending on various samples since it can adjust to variations in the degeneration of sample brain areas. In clinical problems, the PDECNN model has additional diagnostic importance since it can identify sample-specific degraded brain areas based on input samples. This model considers the variability of brain region degeneration levels between input samples, evaluates the degree of degeneration of specific brain regions using an attention mechanism, and selects and integrates brain region features based on the degree of degeneration. Furthermore, by redesigning the classification accuracy performance, we respectively improve it by 4 %, 11 %, and 8 %. Moreover, the degraded brain regions identified by the model show high consistency with the clinical manifestations of AD., Competing Interests: Declaration of competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

We present a four-component relativistic unitary coupled cluster method for atoms and molecules. We have used commutator-based non-perturbative approximation using the "Bernoulli expansion" to derive an approximation to the relativistic unitary coupled cluster method. The performance of the full quadratic unitary coupled-cluster singles and doubles method (qUCCSD), as well as a perturbative approximation variant (UCC3), has been reported for both energies and properties. It can be seen that both methods give results comparable to those of the standard relativistic coupled cluster method. The qUCCSD method shows better agreement with experimental results due to the better inclusion of relaxation effects. The relativistic UCC3 and qUCCSD methods can simulate the spin-forbidden transition with easy access to transition properties. A natural spinor-based scheme to reduce the computational cost of relativistic UCC3 and qUCCSD methods has been discussed., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Lasia spinosa ( L. spinosa ) is widely used in Asian countries for treating various diseases and as a vegetable, yet its bioactive properties remain under-researched. It is traditionally utilized in Ayurveda and the AYUSH system of medicine for its medicinal properties, and commonly used to treat digestive disorders, respiratory issues, and inflammatory conditions. This study aims to identify the phytochemicals in L. spinosa leaves and fruit extracts and evaluate their biological activities. Phytochemicals in methanol extracts of L. spinosa fruits and leaves were identified by GC-MS analysis. Antioxidant and cytotoxic activities were assessed using the DPPH free radical and nitric oxide (NO) scavenging assay and brine shrimp lethality test. Antibacterial activity was evaluated against Shigella boydii , Shigella flexneri , Streptococcus iniae , and Streptococcus dysgalactiae , while antifungal properties were tested against Cercospora beticola and Rhizoctonia solani . Molecular docking was conducted to predict the effectiveness of L. spinosa phytochemicals against NADPH oxidase and the Shigella effector OspG. Nine compounds were detected from both extracts. The methanol leaves extract exhibited superior antioxidant activity compared to the fruit extract, with IC 50 values of 111.81 ± 8.99 µg/ml and 174.81 ± 4.86 µg/ml, respectively, as determined by the DPPH scavenging assay. The nitric oxide (NO) scavenging assay also revealed higher potency in the leaves extract (IC 50  = 138.59 ± 1.50 µg/ml) compared to the fruit extract (IC 50  = 196.47 ± 1.72 µg/ml). Both extracts showed significant antimicrobial activity against all tested microorganisms. In silico studies indicated notable inhibitory activity of all phytochemicals against the target proteins, with Linoelaidic acid and 9-Octadecenamide, (Z)- exhibiting the highest activity against NADPH oxidase (PDB: 2cdu) and Shigella flexneri OspG effector kinase (PDB: 4bvu), respectively. These findings suggest that L. spinosa has potent antioxidant and antimicrobial activities. Compounds from this plant could serve as lead compounds for developing antioxidant and antibacterial agents. However, molecular studies should be addressed., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Modern technology and analysis of emotions play a crucial role in enabling intelligent healthcare systems to provide diagnostics and self-assistance services based on observation. However, precise data predictions and computational models are critical for these systems to perform their jobs effectively. Traditionally, healthcare monitoring has been the primary emphasis. However, there were a couple of negatives, including the pattern feature generating the method's scalability and reliability, which was tested with different data sources. This paper delves into the Discriminant Input Processing Scheme (DIPS), a crucial instrument for resolving challenges. Data-segmentation-based complex processing techniques allow DIPS to merge many emotion analysis streams. The DIPS recommendation engine uses segmented data characteristics to sift through inputs from the emotion stream for patterns. The recommendation is more accurate and flexible since DIPS uses transfer learning to identify similar data across different streams. With transfer learning, this study can be sure that the previous recommendations and data properties will be available in future data streams, making the most of them. Data utilization ratio, approximation, accuracy, and false rate are some of the metrics used to assess the effectiveness of the advised approach. Self-assisted intelligent healthcare systems that use emotion-based analysis and state-of-the-art technology are crucial when managing healthcare. This study improves healthcare management's accuracy and efficiency using computational models like DIPS to guarantee accurate data forecasts and recommendations.

The global diversity of fungi has been estimated between 2 to 11 million species, of which only about 155 000 have been named. Most fungi are invisible to the unaided eye, but they represent a major component of biodiversity on our planet, and play essential ecological roles, supporting life as we know it. Although approximately 20 000 fungal genera are presently recognised, the ecology of most remains undetermined. Despite all this diversity, the mycological community actively researches some fungal genera more commonly than others. This poses an interesting question: why have some fungal genera impacted mycology and related fields more than others? To address this issue, we conducted a bibliometric analysis to identify the top 100 most cited fungal genera. A thorough database search of the Web of Science, Google Scholar, and PubMed was performed to establish which genera are most cited. The most cited 10 genera are Saccharomyces , Candida , Aspergillus , Fusarium , Penicillium , Trichoderma , Botrytis , Pichia , Cryptococcus and Alternaria . Case studies are presented for the 100 most cited genera with general background, notes on their ecology and economic significance and important research advances. This paper provides a historic overview of scientific research of these genera and the prospect for further research. Citation: Bhunjun CS, Chen YJ, Phukhamsakda C, Boekhout T, Groenewald JZ, McKenzie EHC, Francisco EC, Frisvad JC, Groenewald M, Hurdeal VG, Luangsa-ard J, Perrone G, Visagie CM, Bai FY, Błaszkowski J, Braun U, de Souza FA, de Queiroz MB, Dutta AK, Gonkhom D, Goto BT, Guarnaccia V, Hagen F, Houbraken J, Lachance MA, Li JJ, Luo KY, Magurno F, Mongkolsamrit S, Robert V, Roy N, Tibpromma S, Wanasinghe DN, Wang DQ, Wei DP, Zhao CL, Aiphuk W, Ajayi-Oyetunde O, Arantes TD, Araujo JC, Begerow D, Bakhshi M, Barbosa RN, Behrens FH, Bensch K, Bezerra JDP, Bilański P, Bradley CA, Bubner B, Burgess TI, Buyck B, Čadež N, Cai L, Calaça FJS, Campbell LJ, Chaverri P, Chen YY, Chethana KWT, Coetzee B, Costa MM, Chen Q, Custódio FA, Dai YC, Damm U, de Azevedo Santiago ALCM, De Miccolis Angelini RM, Dijksterhuis J, Dissanayake AJ, Doilom M, Dong W, Alvarez-Duarte E, Fischer M, Gajanayake AJ, Gené J, Gomdola D, Gomes AAM, Hausner G, He MQ, Hou L, Iturrieta-González I, Jami F, Jankowiak R, Jayawardena RS, Kandemir H, Kiss L, Kobmoo N, Kowalski T, Landi L, Lin CG, Liu JK, Liu XB, Loizides M, Luangharn T, Maharachchikumbura SSN, Makhathini Mkhwanazi GJ, Manawasinghe IS, Marin-Felix Y, McTaggart AR, Moreau PA, Morozova OV, Mostert L, Osiewacz HD, Pem D, Phookamsak R, Pollastro S, Pordel A, Poyntner C, Phillips AJL, Phonemany M, Promputtha I, Rathnayaka AR, Rodrigues AM, Romanazzi G, Rothmann L, Salgado-Salazar C, Sandoval-Denis M, Saupe SJ, Scholler M, Scott P, Shivas RG, Silar P, Souza-Motta CM, Silva-Filho AGS, Spies CFJ, Stchigel AM, Sterflinger K, Summerbell RC, Svetasheva TY, Takamatsu S, Theelen B, Theodoro RC, Thines M, Thongklang N, Torres R, Turchetti B, van den Brule T, Wang XW, Wartchow F, Welti S, Wijesinghe SN, Wu F, Xu R, Yang ZL, Yilmaz N, Yurkov A, Zhao L, Zhao RL, Zhou N, Hyde KD, Crous PW (2024). What are the 100 most cited fungal genera? Studies in Mycology 108 : 1-411. doi: 10.3114/sim.2024.108.01., Competing Interests: The authors declare that there is no conflict of interest., (© 2024 Westerdijk Fungal Biodiversity Institute.)

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Abstract: Mycosis fungoides (MF) is the most prevalent primary cutaneous T-cell lymphoma, with an indolent or aggressive course and poor survival. The pathogenesis of MF remains unclear, and prognostic factors in the early stages are not well established. Here, we characterized the most recurrent genomic alterations using whole-exome sequencing of 67 samples from 48 patients from Lille University Hospital (France), including 18 sequential samples drawn across stages of the malignancy. Genomic data were analyzed on the Broad Institute's Terra bioinformatics platform. We found that gain7q, gain10p15.1 (IL2RA and IL15RA), del10p11.22 (ZEB1), or mutations in JUNB and TET2 are associated with high-risk disease stages. Furthermore, gain7q, gain10p15.1 (IL2RA and IL15RA), del10p11.22 (ZEB1), and del6q16.3 (TNFAIP3) are coupled with shorter survival. Del6q16.3 (TNFAIP3) was a risk factor for progression in patients at low risk. By analyzing the clonal heterogeneity and the clonal evolution of the cohort, we defined different phylogenetic pathways of the disease with acquisition of JUNB, gain10p15.1 (IL2RA and IL15RA), or del12p13.1 (CDKN1B) at progression. These results establish the genomics and clonality of MF and identify potential patients at risk of progression, independent of their clinical stage., (© 2024 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Three novel bismuth-organic compounds, with the general formula [Bi 2 (HPDC) 2 (PDC) 2 ]·(arene)·2H 2 O (H 2 PDC = 2,6-pyridinedicarboxylic acid; arene = pyrene, naphthalene, and azulene), that consist of neutral dinuclear Bi-pyridinedicarboxylate complexes and outer coordination sphere arene molecules were synthesized and structurally characterized. The structures of all three phases exhibit strong π-π stacking interactions between the Bi-bound PDC/HPDC and outer sphere organic molecules; these interactions effectively sandwich the arene molecules between bismuth complexes and thereby prevent molecular vibrations. Upon UV irradiation, the compounds containing pyrene and naphthalene displayed red and green emission, respectively, with quantum yields of 1.3(2) and 30.8(4)%. The emission was found to originate from the T 1 → S 0 transition of the corresponding arene and result in phosphorescence characteristic of the arene employed. By comparison, the azulene-containing compound displayed very weak blue-purple phosphorescence of unknown origin and is a rare example of T 2 → S 0 emission from azulene. The pyrene- and naphthalene-containing compounds both display radioluminescence, with intensities of 11 and 38% relative to bismuth germanate, respectively. Collectively, these results provide further insights into the structure-property relationships that underpin luminescence from Bi-based materials and highlight the utility of Bi-organic molecules in the realization of organic emission.

The process of identification and management of neurological disorder conditions faces challenges, prompting the investigation of novel methods in order to improve diagnostic accuracy. In this study, we conducted a systematic literature review to identify the significance of genetics- and molecular-pathway-based machine learning (ML) models in treating neurological disorder conditions. According to the study's objectives, search strategies were developed to extract the research studies using digital libraries. We followed rigorous study selection criteria. A total of 24 studies met the inclusion criteria and were included in the review. We classified the studies based on neurological disorders. The included studies highlighted multiple methodologies and exceptional results in treating neurological disorders. The study findings underscore the potential of the existing models, presenting personalized interventions based on the individual's conditions. The findings offer better-performing approaches that handle genetics and molecular data to generate effective outcomes. Moreover, we discuss the future research directions and challenges, emphasizing the demand for generalizing existing models in real-world clinical settings. This study contributes to advancing knowledge in the field of diagnosis and management of neurological disorders.

We undertake a numerical study of the ordering kinetics in the two-dimensional (2D) active Ising model (AIM), a discrete flocking model with a conserved density field coupled to a nonconserved magnetization field. We find that for a quench into the liquid-gas coexistence region and in the ordered liquid region, the characteristic length scale of both the density and magnetization domains follows the Lifshitz-Cahn-Allen growth law, R(t)∼t^{1/2}, consistent with the growth law of passive systems with scalar order parameter and nonconserved dynamics. The system morphology is analyzed with the two-point correlation function and its Fourier transform, the structure factor, which conforms to the well-known Porod's law, a manifestation of the coarsening of compact domains with smooth boundaries. We also find the domain growth exponent unaffected by different noise strengths and self-propulsion velocities of the active particles. However, transverse diffusion is found to play the most significant role in the growth kinetics of the AIM. We extract the same growth exponent by solving the hydrodynamic equations of the AIM.