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Bacteria of the genus Pseudomonas are ubiquitous on Earth due to their great metabolic versatility and adaptation to fluctuating environments and different hosts. Some groups are important animal/human and plant pathogens, whereas others are studied for their biotechnological applications, including bioremediation, biological control of phytopathogens and plant growth promotion. Notably, their adaptability is mediated by various signal transduction systems, with the post-transcriptional Gac-Rsm cascade playing a key role. This pervasive Pseudomonas pathway controls major transitions at the population level, such as motile/sessile lifestyle, primary/secondary metabolism or replicative/infective behaviour. A hallmark of the Gac-Rsm cascade is the participation of small, regulatory, non-coding RNAs of the Rsm clan. These RNAs are synthetised in response to cell-density-dependent autoinducer signals channelled through the GacS/GacA two-component system, and they counteract, by molecular mimicry, the translational control that RNA-binding proteins of the RsmA family exert over hundreds of mRNAs. Rsm RNAs have been investigated in a few Pseudomonas model species, evidencing the presence of a variable number and families of genes depending on the taxonomic clade. However, the global picture of the distribution of these riboregulators at the genus level was unknown until now. We have undertaken a comprehensive survey and annotation of the vast array of gene sequences encoding members of the Rsm RNA clan in 245 complete genomes that cover 28 phylogenomic clades across the entire genus. The properties of the different families of rsm genes, their phylogenetic radiation, as well as the features of their promoters and adjacent regions, are discussed. The novel insights presented in our manuscript will significantly boost research on the biology of these prevalent RNAs in understudied species of the genus Pseudomonas and closely related genera.

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Sarcopenia, characterised by a decline in muscle mass and strength, affects the health of the elderly, leading to increased falls, hospitalisation, and mortality rates. Muscle quality, reflecting microscopic and macroscopic muscle changes, is a critical determinant of physical function. To utilise radiomic features extracted from magnetic resonance (MR) images to assess age-related changes in muscle quality, a dataset of 24 adults, divided into older (male/female: 6/6, 66-79 years) and younger (male/female: 6/6, 21-31 years) groups, was used to investigate the radiomics features of the dorsiflexor and plantar flexor muscles of the lower leg that are critical for mobility. MR images were processed using MaZda software for feature extraction. Dimensionality reduction was performed using principal component analysis and recursive feature elimination, followed by classification using machine learning models, such as support vector machine, extreme gradient boosting, and naïve Bayes. A leave-one-out validation test was used to train and test the classifiers, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the classification performance. The analysis revealed that significant differences in radiomic feature distributions were found between age groups, with older adults showing higher complexity and variability in muscle texture. The plantar flexors showed similar or higher AUC than the dorsiflexors in all models. When the dorsiflexor muscles were combined with the plantar flexor muscles, they tended to have a higher AUC than when they were used alone. Radiomic features in lower-leg MR images reflect ageing, especially in the plantar flexor muscles. Radiomic analysis can offer a deeper understanding of age-related muscle quality than traditional muscle mass assessments.

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Protein-protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a result, we adopted an Aquilla Influenced Shark Smell (AISSO)-based hybrid prediction technique to construct a sequence-dependent PPI prediction model. This model has two stages of operation: feature extraction and prediction. Along with sequence-based and Gene Ontology features, unique features were produced in the feature extraction stage utilizing the improved semantic similarity technique, which may deliver reliable findings. These collected characteristics were then sent to the prediction step, and hybrid neural networks, such as the Improved Recurrent Neural Network and Deep Belief Networks, were used to predict the PPI using modified score level fusion. These neural networks' weight variables were adjusted utilizing a unique optimal methodology called Aquila Influenced Shark Smell (AISSO), and the outcomes showed that the developed model had attained an accuracy of around 88%, which is much better than the traditional methods; this model AISSO-based PPI prediction can provide precise and effective predictions.

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Objective: Music strongly modulates our autonomic nervous system. This modulation is evident in musicians' beat-to-beat heart (RR) intervals, a marker of heart rate variability (HRV), and can be related to music features and structures. We present a novel approach to modeling musicians' RR interval variations, analyzing detailed components within a music piece to extract continuous music features and annotations of musicians' performance decisions. Methods: A professional ensemble (violinist, cellist, and pianist) performs Schubert's Trio No. 2, Op. 100, Andante con moto nine times during rehearsals. RR interval series are collected from each musician using wireless ECG sensors. Linear mixed models are used to predict their RR intervals based on music features (tempo, loudness, note density), interpretive choices (Interpretation Map), and a starting factor. Results: The models explain approximately half of the variability of the RR interval series for all musicians, with R-squared = 0.606 (violinist), 0.494 (cellist), and 0.540 (pianist). The features with the strongest predictive values were loudness, climax, moment of concern, and starting factor. Conclusions: The method revealed the relative effects of different music features on autonomic response. For the first time, we show a strong link between an interpretation map and RR interval changes. Modeling autonomic response to music stimuli is important for developing medical and non-medical interventions. Our models can serve as a framework for estimating performers' physiological reactions using only music information that could also apply to listeners.

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In recent years, research on enjoyment in foreign language (FL) learning has flourished. To help illuminate the existing scope of inquiry and guide future research, this paper presents a systematic review of 118 empirical studies on FL learning enjoyment published between 2014 and 2023. Each study was coded according to its research context, methodological features, and research focus. The results indicate (1) a heavy focus on adult English as a foreign language (EFL) learners whose first languages are Chinese or Persian within traditional classroom learning settings; (2) a strong preference for quantitative methods; and (3) a prominent focus on enjoyment's antecedents and effects. Drawing upon these findings, we recommend that future research (1) addresses the experiences of language learners from diverse demographic backgrounds in a wider variety of learning settings; (2) applies multimodal methods to thoroughly assess the experience of enjoyment from both objective and subjective perspectives; and (3) explores the nature of enjoyable teacher-student or student-student socio-emotional interaction in greater depth.

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Introduction: Breast cancer is a heterogeneous disease comprising various molecular subtypes, including Luminal A, Luminal B, human epidermal growth factor receptor-2 (HER2) positive, and triple negative types, each with distinct biological characteristics and behaviors. Triple negative breast cancer (TNBC) remains a particularly challenging subtype worldwide. Our study aims to evaluate whether Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (18F-FDG PET/CT) parameters, clinical pathological features, and biochemical indicators serve as prognostic risk factors for TNBC. Additionally, we explore correlations between biochemical indicators and 18F-FDG PET/CT parameters. Methods: We conducted a retrospective analysis of 95 TNBC patients who underwent preoperative 18F-FDG PET/CT examinations at Tianjin Medical University Cancer Institute and Hospital from 2013 to 2018. Collected data included 18F-FDG PET/CT parameters, clinical and pathological features, and biochemical indicators. We used Kaplan-Meier survival analysis and multivariate Cox regression analysis to evaluate associations between 18F-FDG PET/CT parameters/biochemical indicators and disease free survival (DFS)/overall survival (OS). The log-rank test determined significant differences in survival curves, and the Spearman correlation coefficient analyzed correlations between quantitative variables. Visualization and analysis were performed using R packages. Results: Among 95 TNBC patients, mean standardized uptake value (SUVmean) was significantly correlated with DFS. Fasting blood glucose (FBG), α- L-fucosylase (AFU) and Creatine kinase (CK) were independent predictors of DFS, while Precursor albumin (PALB) and CK were independent predictors of OS. FBG showed correlations with SUVpeak and SUVmean, and CK was correlated with peak standardized uptake value (SUVpeak). Our results indicated that 18F-FDG PET/CT parameters and biochemical indicators may constitute a new prognostic model for TNBC patients post-surgery. Discussion: We found that SUVmean, FBG, AFU and CK are predictive factors for DFS in TNBC patients post-surgery, while PALB and CK are predictive factors for OS, which prompts us to pay more attention to these indicators in clinical practice. Also 18F-FDG PET/CT parameters and biochemical indicators have potential utility in constituting a new prognostic model for TNBC patients post-surgery.

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INTRODUCTION: Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that primarily affects middle-aged individuals but is increasingly prevalent among the elderly due to longer life expectancies. Treating elderly onset RA (EORA) is challenging for clinicians because of unique disease characteristics, comorbidities, polypharmacy, age-related physiological changes, and limited studies on the safety and efficacy of biological therapies in this population. This review aims to evaluate the use of various biological therapies in elderly RA patients. AREAS COVERED: This narrative review examines various aspects of RA in the elderly using published literature, randomized control trials, meta-analyses, and recommendations from the National Institute for Health and Care Excellence (NICE) and The European Alliance of Associations for Rheumatology (EULAR). EXPERT OPINION: In EORA patients, the initiation of biological therapy is often delayed. Methotrexate remains the first-line treatment for both EORA and young onset RA (YORA). The combination of methotrexate and biological treatment shows comparable safety and efficacy in both EORA and YORA, except for rituximab, which is less effective in patients over 75. For elderly RA patients, biological (b-) disease-modifying antirheumatic drugs (DMARDs) are preferred as the first advanced therapy over targeted synthetic (ts-) DMARDs due to their superior safety profile.

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Metallic alloys of different compositions are basic structures for building different types of nuclear reactors. This study evaluates the nuclear properties for three medium entropy alloys against incident neutrons and gamma radiation. The alloys had different chemical compositions prepared by powder technology and were compared with two stainless steel alloys for use in constructing different parts of nuclear power plant units. The shielding parameters were calculated: linear attenuation coefficient, half-value layer, tenth-value layer, mean free path, effective atomic number (Zeff), effective electronic number, and neutron removal cross-section. The Zeff of all investigated alloys had a range of 25.46-25.93.Sample 1 medium entropy alloy had the lowest neutron absorption feature and the greatest density (7.890 ± 0.323 g/cm3) and Sample 3 medium entropy alloy had the largest neutron absorption feature. The study indicates that medium entropy alloys have potential for enhancing efficiency and safety of nuclear reactors.

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PURPOSE: This study aimed to analyze the association between the primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer (BC) patients using a large population database. METHODS: BC patients screened in the Surveillance, Epidemiology, and End Results (SEER) database were categorized into 6 groups based on primary sites. Descriptive statistics, Kaplan-Meier curves, Cox regression models, forest plots were used to assess the effect of primary sites on overall survival (OS) and breast cancer-specific survival (BCSS). Multivariate Cox proportional analyses were conducted to calculate hazard ratios (HRs) and adjusted subgroups' hazard ratios (AHRs). Nomograms were utilized to predict OS and BCSS. RESULTS: Among 193,043 BC patients, the highest incidence was found in the upper outer quadrant (52.60%). Central portion patients are associated with more clinical features indicating a poor prognosis, and had worse OS and BCSS than other sites. Univariate and multifactorial Cox analyses showed associations between OS/BCSS and various factors. Subgroup analyses revealed differences in OS and BCSS between central portion and upper outer quadrant varied among age, T and N stage. The nomogram was established to predict the survival of central portion BC patients. CONCLUSIONS: Primary tumor site is associated with clinicopathological features and prognosis of BC, may be influenced by age at diagnosis and T and N stage. Central portion BC patients have worse prognosis due to older age at diagnosis, higher T stage and higher likelihood of lymph node metastasis. Early diagnosis and treatment may help to improve survival of central portion BC.

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OBJECTIVE: Air pollution is increasing and threatening human health. The objective of this study is to investigate the population distribution characteristics of elderly osteoporosis fractures in Hebei Province and Xinjiang Uygur Autonomous Region and to analyze the effects of air pollutants on the number of elderly osteoporosis fracture inpatients in the two regions. METHOD: A retrospective collection of elderly osteoporosis fracture cases was conducted in selected hospitals in Hebei Province and Xinjiang Uygur Autonomous Region from January 1, 2018 to December 31, 2022. The chi-square test was used to compare the distributional characteristics of the population in the two regions. Additionally, we used a distributed lag nonlinear model (DLNM) in order to assess the effect of air pollutants on the number of daily hospital admissions of elderly osteoporosis fracture patients in different regions. RESULT: A total of 19,203 elderly osteoporosis fracture patients were included in the study. The average age of these patients was 76.66 ± 7.55 years, and the majority of them were female (13,514 instances, 70.37%). The disparities in age distribution (χ2 = 133.9 p < 0.001), fracture site (χ2 = 62.0 p < 0.001), and hospitalization cost (Z = -15.635 p < 0.001) between the two regions were statistically significant. The lag effect curves of PM2.5, PM10, and NO2 on the number of elderly osteoporosis fracture hospitalizations in Xinjiang Uygur Autonomous Region exhibited a similar pattern resembling a "W"-shaped curve. All three pollutants reached their highest values after a lag time of 14 days (PM2.5: RR = 1.053, 95% CI: 1.031, 1.074; PM10: RR = 1.031, 95% CI: 1.018, 1.043; NO2: RR = 1.125, 95% CI: 1.070, 1.182). In Hebei Province, the largest impacts of PM2.5 and PM10 were observed after a lag of 14 days (PM2.5: RR = 1.022, 95% CI: 1.013, 1.028; PM10: RR = 1.013, 95% CI: 1.008, 1.018). Similarly, the maximum effect of NO2 was observed after a lag of 11 days (RR = 1.020, 95% CI: 1.010, 1.028). CONCLUSION: There were differences in the epidemiological characteristics of hospitalized patients with osteoporosis fractures between the two regions, PM2.5, PM10, and NO2 increased the number of hospitalizations for osteoporosis fractures. Exposure to air pollutants such as PM2.5 increases the risk of osteoporosis fractures in the elderly population.

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Chitinases play an important role in the molting process of insects and are potential targets for the development of green insecticides. Based on the feature that the +1/+2 sites in OfChtI, OfChtII, and OfChi-h have tryptophan residues in mismatch-parallel position, a strategy to introduce indole scaffold into chitinase inhibitors was proposed, and multitarget chitinase inhibitors containing N-methylcarbamoylguanidinyl and indole scaffold were successfully synthesized. The inhibitory activity showed that compound 8u exhibited significant inhibitory activity against OfChtI, OfChtII, and OfChi-h, with IC50 values of 0.7, 0.79, and 0.58 µM, and Ki values of 0.05 ± 0.005, 0.065 ± 0.004, and 0.025 ± 0.006 µM, respectively. In vivo insecticidal activity showed that compounds 8a and 8g exhibited excellent insecticidal activity against Plutella xylostella and Mythimna separata, with LC50 values of 0.79 and 9.17 mg/L against P. xylostella, respectively, and 3.58 and 83.09 mg/L against M. separata, respectively, making them the most potent chitinase inhibitors with in vivo insecticidal activity discovered to date. The inhibition mechanism and binding free energy results suggested that N-methylcarbamoylguanidinyl binds to the -1 catalytic site, while additional interactions acquired by π-π stacking and hydrophobic interactions of the indole scaffold with tryptophan increase the binding affinity of the targets to chitinases. This work provides a new direction for the development of chitinase inhibitors with compounds 8a and 8g potentially serving as promising candidates for pesticide development.

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We present the case of a 59-year-old immunocompetent female with a mild cough, fever, and rash. She was diagnosed with mild pneumonitis caused by Capnocytophaga canimorsus, with no history of dog bites. An indolent clinical course with transmission via canine face licking in immunocompetent individuals is a rare occurrence according to the literature. The diagnosis was made on positive blood cultures and polymerase chain reaction, following which the patient was treated with beta-lactam antibiotics. C. canimorsus is a gram-negative bacterium found in the saliva of dogs and cats. The incidence of human infections is rare, particularly affecting immunocompromised patients exposed to the saliva of these animals. Typical manifestations include severe sepsis, with a high case fatality.

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Activating FLT3 mutations plays a crucial role in leukemogenesis, but identifying the optimal candidates for FLT3 inhibitor therapy remains controversial. This study aims to explore the impacts of FLT3 mutations in pediatric acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and to compare the mutation profiles between the two types to inspire the targeted application of FLT3 inhibitors. We retrospectively analyzed 243 ALL and 62 AML cases, grouping them into FLT3-mutant and wild-type categories, respectively. We then assessed the associations between FLT3 mutations and the clinical manifestations, genetic characteristics, and prognosis in ALL and AML. Additionally, we compared the distinct features of FLT3 mutations between ALL and AML. In ALL patients, those with FLT3 mutations predominantly exhibited hyperdiploidy (48.6% vs. 14.9%, p < 0.001) and higher FLT3 expression (108.02 [85.11, 142.06] FPKM vs. 23.11 [9.16, 59.14] FPKM, p < 0.001), but lower expression of signaling pathway-related genes such as HRAS, PIK3R3, BAD, MAP2K2, MAPK3, and STAT5A compared to FLT3 wild-type patients. There was no significant difference in prognosis between the two groups. In contrast, AML patients with FLT3 mutations were primarily associated with leucocytosis (82.90 [47.05, 189.76] G/L vs. 20.36 [8.90, 55.39] G/L, p = 0.001), NUP98 rearrangements (30% vs. 4.8%, p = 0.018), elevated FLT3 expression (74.77 [54.31, 109.46] FPKM vs. 34.56 [20.98, 48.28] FPKM, p < 0.001), and upregulated signaling pathway genes including PIK3CB, AKT1, MTOR, BRAF, and MAPK1 relative to FLT3 wild-type, correlating with poor prognosis. Notably, internal tandem duplications were the predominant type of FLT3 mutation in AML (66.7%) with higher inserted base counts, whereas they were almost absent in ALL (6.3%, p < 0.001). In summary, our study demonstrated that the forms and impacts of FLT3 mutations in ALL differed significantly from those in AML. The gene expression profiles of FLT3-related pathways may provide a rationale for using FLT3 inhibitors in AML rather than ALL when FLT3 mutations are present.

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Alzheimer's disease (AD) is a neurological condition that progressively impairs cognitive function and results in memory loss. Despite substantial research efforts, little is known about the specific processes driving AD, and there are few proven therapies. Because of their physiological and genetic resemblance to humans, zebrafish (Danio rerio) have become an important model organism for furthering research on AD. This abstract discusses the difficulties faced, looks at the insights currently garnered from zebrafish models, and suggests future research options. AD knowledge has greatly benefited from the use of zebrafish models. Transgenic zebrafish that express human AD-associated genes, such as tau and amyloid precursor protein (APP), display tau neurofibrillary tangles (NFTs) and amyloid-beta (Aß) plaques, two of the disease's main clinical characteristics. These models have clarified the roles of oxidative stress, inflammation, and calcium homeostasis in the course of AD and allowed for the purpose of high-throughput screening of potential therapeutic agents. Understanding the growth and deterioration of neurons has been greatly aided by real-time zebrafish imaging. Fully using zebrafish models in AD research requires addressing a number of issues. The dissimilarities in zebrafish anatomy and physiology from humans, the difficulty of developing models that replicate progressive and late-onset AD (LOAD), and the requirement for standardized procedures to evaluate alterations in zebrafish cognition and behavior are a few issues. Furthermore, variations in the genetic makeup of zebrafish strains might affect the results of experiments. Future directions include developing standardized behavioral assays and cognitive tests, working together to create extensive databases of zebrafish genetic and phenotypic data, and using genetic engineering techniques like CRISPR/Cas9 to create more complex zebrafish models. Combining zebrafish models with other model species helps expedite the conversion of research results into therapeutic applications and offers a more thorough knowledge of AD. To sum up, zebrafish models have made a substantial contribution to Alzheimer's research by offering insightful information on the causes of the illness and possible therapies. By tackling present issues and formulating a planned future path, we can improve the use of zebrafish to decipher the mysteries of Alzheimer's and help create successful treatments.

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Background Chronic kidney disease (CKD) can lead to serious conditions such as anemia and cardiovascular disease, posing a growing global health challenge. End-stage renal disease (ESRD) requires treatments such as dialysis or kidney transplantation. Despite the widespread impact and rising prevalence of CKD and ESRD, comprehensive data remains limited in India. This study seeks to investigate the clinical, socio-demographic, and etiological profiles of CKD patients undergoing hemodialysis at a tertiary care hospital, with the goal of enhancing understanding and improving patient care. Methodology This retrospective cohort study, conducted at a tertiary care center, included 500 CKD patients undergoing hemodialysis, with comprehensive medical records. Data collected covered demographics (age, sex, education, and occupation), CKD etiology, disease duration, hemodialysis duration, viral marker status, blood transfusions, and vascular access details. With continuous variables reported as mean ± standard deviation (SD) and categorical variables as counts (percentages), statistical analysis was carried out using SPSS version 21 (IBM Corp., Armonk, New York, USA). The connections were examined using the Pearson Chi-square test, with P≤0.05 being deemed significant. Results The study revealed that hypertension was the primary cause of CKD in 58% of patients, followed by diabetes mellitus in 13%. A significant 93% of patients tested negative for viral markers such as human immunodeficiency virus (HIV), hepatitis C virus (HCV), and hepatitis B surface antigen (HBsAg). Hemodialysis duration varied, with 68% of patients undergoing dialysis for one to five years. Most patients had two (40%) or three (58%) dialysis sessions per week, and 84% had only one arteriovenous (AV) fistula surgery. Blood transfusions were common, with 62% of patients receiving between one and five transfusions. The gender distribution showed more males (372) than females (201), and the majority of patients were aged between 41 and 60 years. Conclusion This study highlights the importance of early detection and management of CKD, emphasizing preventive health measures, enhanced diagnostic capabilities, and sufficient resource allocation to reduce the disease burden. It also calls for further research into unknown CKD causes and strategies to improve patient care and outcomes.

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Perceiving and reacting to multidimensional objects creates so-called event files via feature binding. Bogon, Thomaschke, and Dreisbach (2017) provided the first evidence for the integration of the feature stimulus duration into such event files. However, their paradigm did not allow for differentiation between stimulus-stimulus and stimulus-response binding. The present study used a classification task with many-to-one mappings to examine the integration of stimulus and response features independently. Experiment 1 used a pitch classification task. Participants had to respond with a left keypress to a low and a very low sine tone and with a right keypress to a high and very high sine tone. The four sine tones were presented for either a short or long duration, resulting in a total of eight stimuli. As an indicator of binding, we used partial repetition costs (better performance when both pitch/response and duration repeat or shift relative to partial repetitions). Results of Experiment 1 indicate stimulus-response binding and no stimulus-stimulus binding. In Experiment 2, instead of classifying the pitch of artificial sine tones, participants had to classify the type of musical instruments that produced the stimulus tones. Results replicated evidence for stimulus-response binding but also provided indications for stimulus-stimulus binding. Potential reasons for this result pattern and the relevance of duration in a musical context as one potential moderator of stimulus-stimulus bindings are discussed.

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Background: Prominent epicanthus could not only diminish the eyes' aesthetics but may be deceptive for its typical appearance of pseudo-esotropia. This study aims to apply a deep learning model to characterize the periocular morphology for preliminary identification. Methods: This prospective study consecutively included 300 subjects visiting the ophthalmology department in a tertiary referral hospital. Children aged 7-18 years with simple epicanthus or concomitant esotropia and healthy volunteers who were age- and gender-matched were eligible for inclusion. Multiple metrics were extracted automatically and manually from facial images to characterize the periocular morphology and binocular symmetry. The dice coefficient (Dice), intraclass correlation coefficient (ICC), and Bland-Altman biases were calculated to evaluate their consistency. The receiver operating characteristic (ROC) curve determined the cut-off values of symmetry indexes (SIs) for distinguishing concomitant esotropia subjects from epicanthus ones. Results: The Dice for eyelid and cornea segmentation were 0.949 and 0.944, respectively. The ICCs of the two measurements ranged from 0.898 to 0.983. Biases ranged from 0.16 to 0.74 mm. The periocular morphology of epicanthus eyes was significantly different from the normal ones, including palpebral fissure width (21.41±1.53 vs. 24.45±1.82 mm; P<0.01), and palpebral fissure height (8.91±1.37 vs. 9.60±1.25 mm; P<0.01). The ROC analysis yielded an area under the curve of 0.971 [95% confidence interval (CI): 0.950-0.991] with SI for distinguishing esotropia subjects. Its optimal cut-off value was 1.296 with 0.920 sensitivity and 0.910 specificity. Conclusions: Our study established a standard deep learning system for characterizing the periocular morphology of epicanthus and esotropia eyes with great accuracy. This objective method could be generalized to other periocular morphological assessments for clinical care.

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Objective: Goal of the study was to systematically review competitive advantages of medical devices for glucose monitoring in diabetic patients. Method: The review is done systematically according to SALSA criteria and PRISMA guidelines. The search for eligible articles was held from February 16th 2023 to March 1st 2023 in Russian and English languages. The results were synthesized narratively, tabularly, and visually. The search was conducted in the following databases of scientific literature: PubMed, IEEE Xplore, Google Scholar, CyberLeninka, and eLibrary. Results: Twenty-two out of fifty-two manuscripts met the inclusion criteria. The most promising and advantageous characteristics of the evaluated devices, as identified by researchers, include the following: the capability for noninvasive examination; features that facilitate use by patients with fine motor, hearing, and visual impairments; add-ons and software designed to improve patient compliance, including in pediatric populations; and device attributes that enhance the speed and accuracy of analysis while being free of iatrogenic effects. Conclusions: With increasing prevalence of diabetes, glycemic control is crucial for preventing complications. The market offers numerous glucose monitoring devices (GMDs) with varying features, making selection challenging. Our study systematically categorized the strengths of each GMD model for diabetic patients, aiding informed device selection.

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Objective: This study examined the impact of prior familiarity with automated external defibrillator (AED) models on the time of defibrillation and the emotional experiences of laypersons. Methods: We conducted a randomized cross over simulation study with 123 participants to assess their reactions to both familiar and unfamiliar AED models. The time to first defibrillation was measured using three different AED training models, two of which were previously unknown to the participants. Additionally, semi-structured interviews were held with the participants to gather further insights. Results: Participants took longer to initiate defibrillation with unfamiliar (M = 34 s) AEDs compared to familiar (M = 27 s) ones. This delay was accompanied by feelings of confusion, nervousness, and anxiety. Factors such as the design of the AED covers, electrodes, and buttons were identified as sources of confusion. Nonetheless, clear instructions and similarities between devices helped facilitate their use. Conclusion: The findings suggest that AED design and familiarity with different AED designs may affect performance by laypersons. To improve user confidence, it would be useful to familiarize users with a variety of AED models as part of training initiatives. Understanding the impact of AED familiarity on rescuer's response can guide CPR training strategies and improve outcomes for OHCA. As more AED models become available to the public, the user-friendliness of AEDs may also be improved. It is beneficial for AED manufacturers to consider the results of research when developing new models.

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OBJECTIVE: This study aims to explore possible susceptibility genes and clinical features for systemic lupus erythematosus (SLE) patients in a Chinese population. METHODS: Expanding on the results of a prior single-center observational study involving 60 systemic lupus erythematosus patients, a subsequent single-center prospective observational study was conducted on SLE patients undergoing treatment at Nanfang Hospital Affiliated to Southern Medical University from 2021 to 2023. The identification process for drug-related target genes entailed an extensive search across PharmGKB (https://www.pharmgkb.org/), the Clinical Pharmacogenetics Implementation Consortium (CPIC),and PubMed literature databases, to pinpoint common drugs and target single nucleotide polymorphisms(SNPs)for SLE. Blood samples were individually collected and genotyped using MassARRAY® high-throughput nucleic acid mass spectrometry. Genotype frequency differences were assessed through Chi-square tests against both the larger East Asian population as well as kidney transplant recipients. Data collection relied on electronic medical records, encompassing demographic details(age, gender),medication regimens(hormones, NSAIDs, hydroxychloroquine, DMARDs, biologic agents, stomach medications, calcitriol, etc.),laboratory indicators(RF, Anti-CCP antibody, ESR, CRP, anti-ANA antibodies, dsDNA antibodies, anti-SM antibodies, S m. RNP antibodies, A LT, ALB, CR, UA, WBC, PLT, HGB, Ca, K, Glu, CHOL, TG, LDL-C, HDL-C) and lupus activity scores(SLEDAI-2K). Possible disease susceptibility genes were categorized, and SPSS26 software facilitated statistical analyses. RESULTS: The research encompassed a total of 137 SLE patients along with 50 SNPs. After conducting statistical analyses, it emerged that there existed significant disparities in CYP2D6 gene (rs1065852) distribution when compared against allele mutation rates within both East Asian populations (p < .05) and kidney transplant patients(p < .05). Wild-type gene (GG) constituted 14% of cases while mutant gene (GA + AA) constituted 86%. Allele mutation rate (A63.6%) was significantly higher among SLE patients (RR = 0.802; p = .0355). Furthermore, the variant rs1065852 genotype (GA + AA) demonstrated significant associations with lower CRP levels, higher HGB levels, and higher HDL-C levels (p < 0 0.05). CONCLUSION: The metabolic enzyme CYP2D6 may be used as susceptibility gene for predicting systemic lupus erythematosus and are correlated with CRP and other indicators.