Revisiting dexamethasone dosage in COVID-19 management

The ongoing coronavirus disease 2019(COVID-19)pandemic has necessitated rapid advancements in therapeutic strategies,with dexamethasone emerging as a key treatment for severe cases.This editorial discusses the systematic review conducted by Sethi et al,published in the World Journal of Virology.The review critically examines the efficacy and safety of varying dosages of dexamethasone in severe COVID-19 patients,providing a comprehensive meta-analysis that underscores the current clinical recommendations favoring a low-dose regimen.Despite these findings,the review highlights the potential benefits of tailored dosages for specific patient subgroups,suggesting a need for personalized treatment approaches.This editorial expands on the implications of these findings,advocating for the integration of evolving clinical data into treatment protocols and calling for further research into patient-specific responses to therapy.It emphasizes the importance of adaptability and precision in pandemic response,urging the medical community to consider both the robustness of existing evidence and the potential for innovative approaches to enhance patient outcomes in the face of global health challenges.

Cognitive impairment in patients with bipolar disorder alone versus those with bipolar disorder comorbid with borderline personality disorder

BACKGROUND Bipolar disorder(BD)is a severe mental illness.BD often coexists with borderline personality disorders,making the condition more complex.AIM To explore the differences in cognitive impairment between patients with BD and those with BD comorbid with borderline personality disorder.METHODS Eighty patients with BD and comorbid borderline personality disorder and 80 patients with BD alone were included in groups A and B,respectively,and 80 healthy volunteers were included as controls.Cognitive function in each group was evaluated using the Chinese version of the repeatable battery for the assess-ment of neuropsychological status(RBANS),the Stroop color-word test,and the Wechsler intelligence scale-revised(WAIS-RC).RESULTS The indices of the RBANS,Stroop color-word test,and WAIS-RC in groups A and B were significantly lower than those of the control group(P<0.05).Group A had significantly longer Stroop color-word test times for single-character,single-color,double-character,and double-color,lower scores of immediate memory,visual breadth,verbal function dimensions and total score of the RBANS,as well as lower scores of verbal IQ,performance IQ,and overall IQ of the WAIS-RC compared with group B(P<0.05).Compared to group B,group A exhibited significantly longer single-character time,single-color time,double-character time,and double-color time in the Stroop color-word test(P<0.05).CONCLUSION The cognitive function of patients with BD complicated with borderline personality disorder is lower than that of patients with BD.

Personality Traits and Cognitive Determinants——An Empirical Investigation of the Use of Smartphone Security Measures

In the last years, increasing smartphones’ capabilities have caused a paradigm shift in the way of users’ view and using mobile devices. Although researchers have started to focus on behavioral models to explain and predict human behavior, there is limited empirical research about the influence of smartphone users’ individual differences on the usage of security measures. The aim of this study is to examine the influence of individual differences on cognitive determinants of behavioral intention to use security measures. Individual differences are measured by the Five-Factor Model;cognitive determinants of behavioral intention are adapted from the validated behavioral models theory of planned behavior and technology acceptance model. An explorative, quantitative survey of 435 smartphone users is served as data basis. The results suggest that multiple facets of smartphone user’s personalities significantly affect the cognitive determinants, which indicate the behavioral intention to use security measures. From these findings, practical and theoretical implications for companies, organizations, and researchers are derived and discussed.

Conscious, Explicit Memory, Implicit Memory, and Instincts as the Four-Component Mind for the Mental Origins of Psychotherapy and Personality

This paper proposes that conscious, explicit memory, implicit memory, and instincts constitute the four-component mind for the mental origins of psychotherapy and personality. The mental origin of the personality theories including the big five personality traits, the MBTI, the social style model, the Hofstede’s cultural dimensions, and the Schwartz’s theory of basic human values is from the unconscious instincts (the six social and three mental protective instincts). The three mental protective instincts that contain the three instinctive countermeasures against the three adversities are hyperactivity countermeasure against danger, phobia countermeasure against unfamiliarity-uncertainty, and comforter countermeasure against hardship. Each countermeasure is regulated (moderated) by a regulator to minimize overactive countermeasure as physical regulator to minimize overactive immunity in physical immune system. Severe adversities and ineffective regulators over-activate protective countermeasures to generate overactive countermeasures as overactive hyperactivity, overactive phobia, and overactive comforter, corresponding to dramatic-impulsive cluster, anxious-fearful cluster, and odd-eccentric cluster, respectively for personality-mental disorders in the DSM-5. Such disordered behavioral habits are stored in unconscious implicit memory which generates disordered thought patterns in pre-conscious explicit memory. For psychotherapy, cognitive behavioral therapy (CBT) normalizes disordered thought patterns in explicit memory to normalize disordered behavioral habit memory in implicit memory through the repetitive training in normalizing thought patterns, feelings, and behaviors. For psychotherapy, mindfulness meditation strengthens conscious attention (working memory) to normalize disordered behavioral habit memory through the repetitive training in directing conscious attention to the breath or body. In conclusion, the mental origin of personality-mental disorders is from the overactive mental protective instincts. The mental origin of psychotherapy is from therapeutic implicit memory and conscious attention for CBT and mindfulness meditation, respectively. The mental origin of personality is from the unconscious instincts. Therefore, the four-component mind of conscious, explicit memory, implicit memory, and instincts explains the origin, the storage, and the normalization of personality-mental disorders for psychotherapy, and provides the mental origin of personality.

Effects of Depth of Needle Insertion with Risperidone Long-Acting Injectable in Persons with Schizophrenia: A Randomized Double-Blind Study

In some cases, if the insertion depth is shallower than expected, intramuscular (IM) injection of risperidone long-acting injectable (RLAI) may not penetrate the muscle fascia. However, if needle insertion depth is deeper than anticipated, needle penetration may cause damage to nerves, arteries and veins. Few clinical studies were done to evaluate the depth of needle length insertion reaching the intended gluteal muscle. The aim of this study was to evaluate the suitable depth of injecting RLAI. Twenty-six patients with schizophrenia were treated with RLAI, and randomly divided into two groups: 50 mm needle inserted group (Group-D, deep insertion, n = 13) and 20 mm needle insertion group (Group-S, shallow insertion, n = 13). For Group-S, the needle length was marked with a spacer at exactly 20 mm. Injections were performed by the psychiatrist or nurse, alternating between the two gluteal sites by double-cross method every two weeks. Clinical psychotic symptoms and injection site reactions were recorded throughout the study period. Experienced psychologists who were blinded from the needle-length experimental variable evaluated patients’ psychotic symptoms using the Positive and Negative Syndrome Scale (PANSS) every two weeks. The plasma 9-hydroxyrisperidone (9-OH-RIS) concentrations were measured every two weeks;comparison data were determined on the 8th week and the 14th week. No significant difference was observed in 9-OH-RIS concentrations, psychotic symptoms, injection site skin reactions of subjects in both groups. However, in Group-D, injection site adverse reactions were confirmed in two subjects (15%). In Group-S, injection site reactions were confirmed in six subjects (46%). Although effective 9-OH-RIS concentrations were obtained with the insertion using both depth, it was concluded that the 50 mm insertion length was more suitable for dorsogluteal IM injections in adult patients with schizophrenia as demonstrated by the incidence of local adverse skin reactions.

Relationship of Smartphone Dependence to General Health Status and Personality Traits among University Students

We investigated associations between smartphone dependence and general health status or personality traits. To 197 medical university students, we administered a set of self-reporting questionnaires designed to evaluate these parameters. For males, smartphone dependence positively correlated with somatic symptoms, anxiety and insomnia, and emotional instability, and negatively correlated with agreeableness. For females, smartphone dependence positively correlated with somatic symptoms, severe depression, and extraversion, and negatively correlated with social dysfunction. These findings suggest that smartphone dependence may be associated with general health status or personality traits and that there may be a gender difference in these associations.

No More Excuses - Personality Traits and Academic Dishonesty in Online Courses

Academic dishonesty is a disturbing issue in higher education that has been worsening over the years, especially with the appearance of the internet and the e-learning education. This new technology exposes students to the opportunity of using online bank exams and term papers and increases their tendency to cheat. This study investigates student academic dishonesty in the context of traditional and distance-learning courses in higher education. Data from 1,365 students enrolled in academic institutes in the U.S.A and Israel were surveyed to assess their personality and their willingness to commit various acts of academic misconduct. The findings indicate that in both countries dishonest behaviors are greater in face-to-face courses than in online courses. In addition, both American and Israeli students identified with the personality trait of Agreeableness showed a negative correlation with academic dishonesty. Furthermore, Israeli students identified with the personality traits of Conscientiousness and Emotional Stability demonstrated a negative correlation with academic dishonesty. In contrast, the personality trait of Extraversion among American students was found in a positive correlation with academic misconduct. Implications for further research are discussed.

Analyzing Semantic Creation on Homophones and Phonograms of Chinese from Personal Experiences

This article mainly talk about the creating using of homophones and phonograms of Chinese. The writer give us a brief introduction of homophones and phonograms from a normal view, and it mainly strengthens the particular features of these semantic phenomenon through illustrating some examples that come from the experiences of writer, which is different from the normal instance and it possessing a specific actual significant. While it introduces the reasons of this kind of particular semantic creation, many real particular experiences also exemplified.

Personal Thermal Management by Radiative Cooling and Heating

Maintaining thermal comfort within the human body is crucial for optimal health and overall well-being.By merely broadening the setpoint of indoor temperatures,we could significantly slash energy usage in building heating,ventilation,and air-conditioning systems.In recent years,there has been a surge in advancements in personal thermal management(PTM),aiming to regulate heat and moisture transfer within our immediate surroundings,clothing,and skin.The advent of PTM is driven by the rapid development in nano/micro-materials and energy science and engineering.An emerging research area in PTM is personal radiative thermal management(PRTM),which demonstrates immense potential with its high radiative heat transfer efficiency and ease of regulation.However,it is less taken into account in traditional textiles,and there currently lies a gap in our knowledge and understanding of PRTM.In this review,we aim to present a thorough analysis of advanced textile materials and technologies for PRTM.Specifically,we will introduce and discuss the underlying radiation heat transfer mechanisms,fabrication methods of textiles,and various indoor/outdoor applications in light of their different regulation functionalities,including radiative cooling,radiative heating,and dual-mode thermoregulation.Furthermore,we will shine a light on the current hurdles,propose potential strategies,and delve into future technology trends for PRTM with an emphasis on functionalities and applications.

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

Analysis of the Positive Personalities of Scarlett in Gone with the Wind

Gone with the Wind,the masterpiece of the Margaret,M who has spent about ten years on writing this novel and it takes over half a year of her to verify the specific time and place of the involved historical event.Once the masterpiece is published on June 30,1936,it soon broke several records in sales of American publishing;later,it won the prize of Pulitzer and Association of American publishers.While the leading lady of this novel,Scarlett,become an object of admiration among thousands of people.What attract the readerséyes deeply is her unique origin,outstanding features and noble actions.In the meantime,the charming personality of Margaret's Scarlett has conquered us.She is strong to the difficulties;she is persistent to her love;and she is witty to her family.She is the strongest among the people who has endured the hardship as her no matter she has suffered from the war,the poor and leaving her family.What makes her be responsible to the Taylor Manor is her braveness.At the end of the story,she still tells us:tomorrow is another day! We admire her positive attitude to life,and this is why the female character can be everlasting.

Framework for Personalized Chronic Pain Management:Harnessing AI and Personality Insights for Effective Care

This paper introduces a cutting-edge framework for personalized chronic pain management,leveraging the power of artificial intelligence(AI)and personality insights.It explores the intricate relationship between personality traits and pain perception,expression,and management,identifying key correlations that influence an individual’s experience of pain.By integrating personality psychology with AI-driven personality assessment,this framework offers a novel approach to tailoring chronic pain management strategies for each patient’s unique personality profile.It highlights the relevance of well-established personality theories such as the Big Five and the Myers-Briggs Type Indicator(MBTI)in shaping personalized pain management plans.Additionally,the paper introduces multimodal AI-driven personality assessment,emphasizing the ethical considerations and data collection processes necessary for its implementation.Through illustrative case studies,the paper exemplifies how this framework can lead to more effective and patient-centered pain relief,ultimately enhancing overall well-being.In conclusion,the paper positions the need of an“AI-Powered Holistic Pain Management Initiative”which has the potential to transform chronic pain management by providing personalized,data-driven solutions and create a multifaceted research impact influencing clinical practice,patient outcomes,healthcare policy,and the broader scientific community’s understanding of personalized medicine and AI-driven interventions.

White matter abnormalities in young males with antisocial personality disorder Evidence from voxel-based morphometry-diffeomorphic anatomical registration using exponentiated lie algebra analysis

Voxel-based morphometry-diffeomorphic anatomical registration using exponentiated lie algebra analysis was used to investigate the structural characteristics of white matter in young males with antisocial personality disorder （APD） and healthy controls without APD. The results revealed that APD subjects, relative to healthy subjects, exhibited increased white matter volume in the bilateral prefrontal lobe, right insula, precentral gyrus, bilateral superior temporal gyrus, right postcentral gyrus, right inferior parietal Iobule, right precuneus, right middle occipital lobe, right parahippocampal gyrus and bilateral cingulate, and decreased volume in the middle temporal cortex and right cerebellum. The white matter volume in the medial frontal gyrus was significantly correlated with antisocial type scores on the Personality Diagnostic Questionnaire in APD subjects. These experimental findings indicate that white matter abnormalities in several brain areas may contribute to antisocial behaviors in APD subjects.

Web-based GIS System for Real-time Field Data Collection Using Personal Mobile Phone

Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.

Mutations in Ras homolog family member A in patients with peripheral T-cell lymphoma and implications for personalized medicine

Genome sequencing has revealed frequent mutations in Ras homolog family member A(RHOA)among various cancers with unique aberrant profiles and pathogenic effects,especially in peripheral T-cell lymphoma(PTCL).The discrete positional distribution and types of RHOA amino acid substitutions vary according to the tumor type,thereby leading to different functional and biological properties,which provide new insight into the molecular pathogenesis and potential targeted therapies for various tumors.However,the similarities and discrepancies in characteristics of RHOA mutations among various histologic subtypes of PTCL have not been fully elucidated.Herein we highlight the inconsistencies and complexities of the type and location of RHOA mutations and demonstrate the contribution of RHOA variants to the pathogenesis of PTCL by combining epigenetic abnormalities and activating multiple downstream pathways.The promising potential of targeting RHOA as a therapeutic modality is also outlined.This review provides new insight in the field of personalized medicine to improve the clinical outcomes for patients.

Personalized treatment of perihilar cholangiocarcinoma based on tumor genetic and molecular characteristics

This editorial discusses the article written by Tchilikidi et al that was published in the latest edition of the World Journal of Gastrointestinal Surgery.Genetic and molecular profiling of perihilar cholangiocarcinoma(pCCA)has identified a number of key abnormalities that drive tumor growth and spread,including pyruvate kinase M2,proline rich 11,and transcription factor 7,etc.pCCA has specific genetic and molecular features that can be used to develop personalized treatment plans.Personalized treatment approaches offer new opportunities for effectively targeting the underlying drivers of tumor growth and progression.The findings based on tumor genetic and molecular characteristics highlight the importance of developing personalized treatment strategies.

Association between Job Satisfaction and Stress or Depressive Symptom of Employed Persons with Disabilities:Findings from the Panel Survey of Employment for the Disabled 2016–2023

Background:This study conducted a longitudinal analysis of the association between job satisfaction and stress or depressive symptoms of employed persons with disabilities(PWDs)based on the data from the 1st to 8th Pannel Survey of Employment for the Disabled(PSED).Methods:After excluding missing values,data on 1614 participants at baseline(1st wave)were analyzed using the chi-square test and generalized estimating equation(GEE)model for data from 1st to 8thPSED.Results:It was found that for each one-unit increase in the job satisfaction score,the stress scale decreased by 0.004(B:−0.004,95%CI:−0.006–−0.002,p-value:<0.0001).Compared to the very high job satisfaction group,the low job satisfaction group was more likely to experience perceived stress(odds ratio[OR]:2.127,p-value:0.001)and experience depressive symptoms(OR:3.557,p-value<0.0001).Furthermore,in terms of the overall satisfaction with their current job among the PWDs,compared to the‘satisfied’group,the‘unsatisfied’group had higher perceived stress(OR:1.593,p-value<0.0001)and depressive symptoms(OR:2.688,p-value<0.0001).Conclusions:There was a close association between job satisfaction and stress or depressive symptoms among employed PWDS.This study’s findings may serve as foundational research to support improving mental health in this population.In addition,it is anticipated that these findings can be used as evidence to improve the work environment for PWDs within the context of Korean corporate culture.

Justification of and Response to the Specificity of Workers’Personality Rights

The pervasive existence of subordination in the work-place endows workers’personality rights with a distinct specificity that differs from other civil subjects.The specificity of workers’per-sonality rights is primarily manifested in three aspects:the exercise of rights is restricted by the employer;personality rights infringements often accompany violations of workers’economic property rights;and the scope of rights is not limited to the duration of employment.To respond to the specificity arising in the labor domain,certain disputes concerning workers’personality rights should be handled through la-bor dispute resolution procedures.In individual cases,judicial author-ities should differentiate among protection levels based on the specific type of personality rights involved,with a focus on examining the rea-sons,methods,and extent of the employer’s restrictive actions,thereby establishing a practical and reasonable review system.。

Personalized medicine and opioid use disorder

Opioid use disorder(OUD)is a major public health problem affecting millions of people worldwide.Although OUD is a chronic and relapsing disorder,a variety of pharmacological and non-pharmacological interventions are available.Medication-assisted treatment of OUD generally relies on competition for opioid receptors against the addictive substance.The mechanisms of this competition are to block or inactivate the opioid receptor or activate the receptor with a substance that is intermittent or long acting.Methadone and buprenorphine are two United States Food and Drug Administration-approved medications that have long-term positive effects on the health of opioid-dependent individuals.Although clinical studies of drugs generally demonstrate efficacy in thousands of people and toxicity is excluded,it cannot be predicted whether the given drug will cause side effects in one of the patients at the treatment dose.Individual differences can be explained by many biological and environmental factors.Variations in genes encoding drug metabolism or cellular drug targets significantly explain the variability in drug response between individuals.Therefore,for the effects of candidate genes to be accepted and included in individual treatment protocols,it is important to repeat studies on individuals of different ethnic backgrounds and prove a similar effect.

Transforming Healthcare:AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

In the rapidly evolving landscape of healthcare,the integration of Artificial Intelligence(AI)and Natural Language Processing(NLP)holds immense promise for revolutionizing data analytics and decision-making processes.Current techniques for personalized medicine,disease diagnosis,treatment recommendations,and resource optimization in the Internet of Medical Things(IoMT)vary widely,including methods such as rule-based systems,machine learning algorithms,and data-driven approaches.However,many of these techniques face limitations in accuracy,scalability,and adaptability to complex clinical scenarios.This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the IoMT.Through the integration of advanced data analytics methodologies with NLP capabilities,we propose a comprehensive framework designed to enhance personalized medicine,streamline disease diagnosis,provide treatment recommendations,and optimize resource allocation.Using a systematic methodology data was collected from open data repositories,then preprocessed using data cleaning,missing value imputation,feature engineering,and data normalization and scaling.Optimization algorithms,such as Gradient Descent,Adam Optimization,and Stochastic Gradient Descent,were employed in the framework to enhance model performance.These were integrated with NLP processes,including Text Preprocessing,Tokenization,and Sentiment Analysis to facilitate comprehensive analysis of the data to provide actionable insights from the vast streams of data generated by IoMT devices.Lastly,through a synthesis of existing research and real-world case studies,we demonstrated the impact of AI-NLP fusion on healthcare outcomes and operational efficiency.The simulation produced compelling results,achieving an average diagnostic accuracy of 93.5%for the given scenarios,and excelled even further in instances involving rare diseases,achieving an accuracy rate of 98%.With regard to patient-specific treatment plans it generated them with an average precision of 96.7%.Improvements in early risk stratification and enhanced documentation were also noted.Furthermore,the study addresses ethical considerations and challenges associated with deploying AI and NLP in healthcare decision-making processes,offering insights into risk-mitigating strategies.This research contributes to advancing the understanding of AI-driven optimization algorithms in healthcare data analytics,with implications for healthcare practitioners,researchers,and policymakers.By leveraging AI and NLP technologies in IoMT environments,this study paves the way for innovative strategies to enhance patient care and operational effectiveness.Ultimately,this work underscores the transformative potential of AI-NLP fusion in shaping the future of healthcare.