Traditional Clinical Approach Research Articles

Extreme elevations of donor-derived cell-free DNA increases the risk of chronic lung allograft dysfunction and death, even without clinical manifestations of disease.

Lung transplant recipients are traditionally monitored with pulmonary function testing (PFT) and lung biopsy to detect post-transplant complications and guide treatment. Plasma donor-derived cell free DNA (dd-cfDNA) is a novel molecular approach of assessing allograft injury, including subclinical allograft dysfunction. The aim of this study was to determine if episodes of extreme molecular injury (EMI) in lung transplant recipients increases the risk of CLAD or death. This multicenter prospective cohort study included 238 lung transplant recipients. Serial plasma samples were collected for dd-cfDNA measurement by shotgun sequencing. EMI was defined as a dd-cfDNA above the third quartile of levels observed for acute rejection (dd-cfDNA level of ≥ 5% occurring after 45 days post-transplant). EMI was categorized as Secondary if associated with co-existing acute rejection, infection or PFT decline; or Primary if not associated to these conditions. EMI developed in 16% of patients at a median 343.5 (IQR: 177.3-535.5) days post-transplant. Over 50% of EMI episodes were classified as Primary. EMI was associated with an increased risk of severe CLAD or death (HR: 2.52, 95% CI: 1.10 - 3.82, p= 0.024). The risk remained consistent for Primary EMI (HR: 2.34, 95% CI 1.18-4.85, p=0.015). Time to first EMI episode was a significant predictor of the likelihood of developing CLAD or death (AUC=0.856, 95% CI =.805-908, p<.001). Episodes of EMI in lung transplant recipients are often isolated and not detectable with traditional clinical monitoring approaches. EMI is associated with an increased risk of severe CLAD or death, independent of concomitant transplant complications.

Replace or Regenerate? Diverse Approaches to Biomaterials for Treating Corneal Lesions.

The inner structures of the eye are protected by the cornea, which is a transparent membrane exposed to the external environment and subjected to the risk of lesions and diseases, sometimes resulting in impaired vision and blindness. Several eye pathologies can be treated with a keratoplasty, a surgical procedure aimed at replacing the cornea with tissues from human donors. Even though the success rate is high (up to 90% for the first graft in low-risk patients at 5-year follow-up), this approach is limited by the insufficient number of donors and several clinically relevant drawbacks. Alternatively, keratoprosthesis can be applied in an attempt to restore minimal functions of the cornea: For this reason, it is used only for high-risk patients. Recently, many biomaterials of both natural and synthetic origin have been developed as corneal substitutes to restore and replace diseased or injured corneas in low-risk patients. After illustrating the traditional clinical approaches, the present paper aims to review the most innovative solutions that have been recently proposed to regenerate the cornea, avoiding the use of donor tissues. Finally, innovative approaches to biological tissue 3D printing and xenotransplantation will be mentioned.

Integrating Bioinformatics in Cervical Cancer Research: A Comprehensive Review

In this comprehensive review, we delve into the transformative impact of bioinformatics in cervical cancer research, emphasizing its role in shifting from traditional clinical and pathological approaches to a nuanced molecular and genetic understanding. We explore the evolution of cervical cancer research, highlighting the pivotal transition marked by the identification of human papillomavirus (HPV) and the subsequent advancements in screening and vaccination. Central to this review is the elucidation of bioinformatics' contribution in identifying gene signatures, prognostic markers, and differentially expressed genes, along with the analysis of molecular pathways critical in the progression of cervical cancer. We also examine the methodological intricacies of bioinformatics, from data retrieval and preparation through differential gene expression analysis, to more sophisticated techniques like Gene Set Enrichment and Protein-Protein Interaction Network Analysis. Despite the significant strides made, we acknowledge the challenges in integrating bioinformatics findings into clinical practice and propose future directions towards personalized medicine. This review underscores the pivotal role of bioinformatics in enhancing our understanding of cervical cancer and paves the way for novel diagnostic and therapeutic strategies, ultimately aiming to improve patient care and survival rates.

An Integrative Perspective on Understanding Human Functioning: Positive Clinical Psychology

The number of studies conducted with a holistic perspective as an alternative to the traditional clinical psychology approach has increased. It is noteworthy that studies examine the effects of positive concepts on human health in addition to discomfort. In this study, it was aimed to examine four concepts that are frequently researched in positive psychology, namely well-being, psychological resilience, hope and coping in an integrative context. Also, it was aimed to give information about the positive clinical psychology approach and the studies which investigate these four positive concepts. Studies were searched through PsycARTICLE, EBSCO and Pubmed electronic databases. Totally 208 studies were reached and 26 articles were included in this review article. As a result, the effective results in treatment of psychological disorders and increase of well-being of an individual with positive psychology interventions suggest that it is important to expand the positive perspective in clinical psychology. It is thought that it may be clinically important that the presence/increase of positive concepts as well as the absence/decrease of psychopathologies should be one of the treatment targets of mental health specialists. It is hoped that adopting an integrative perspective in future studies will enrich empirical research in the field of psychotherapy.

Apheleia‐001: A novel prescreening study designed to enrich and accelerate Alzheimer’s disease clinical trials by efficiently identifying trial‐eligible participants determined to have a high probability of study inclusion, including amyloid positivity

AbstractBackgroundThe clinical development ecosystem cannot support the current demand for participants needed in Alzheimer’s disease clinical trials which is further disrupted by: 1) high screen fail rates (≥80‐90%); 2) lengthy screening visits constraining site resources; 3) unnecessary participant burden. The field demands a unique approach to optimize site resource utilization, participant/caregiver time, and overall development costs. Apheleia‐001 will identify patients with a high probability of meeting study‐specific eligibility criteria for a therapeutic Alzheimer’s disease clinical trial.MethodApheleia‐001 prescreens potential participants using paper and digital cognitive tests, demographic and medical information, and blood biomarkers. Apheleia‐001 procedures are completed in &lt;2 hours and they minimize both site and participant burden. Participants eligible through Apheleia‐001 are referred to an early phase therapeutic AD trial.Apheleia‐001 will enroll ∼1600 participants across 28 clinical trial sites in both North America and Europe with an expected 24‐month enrollment period.ResultApheleia‐001 is currently open for enrollment and data is being collected. As of 18Jan2023, Apheleia‐001 has completed 300+ prescreens and has identified over 60 trial eligible participants. Of the 300+ prescreened, 35% have identified as an underrepresented minority (URM). It is projected that the Apheleia pre‐screener will ultimately reduce the screen failure rate of a specific sponsor clinical trial by up to 50%.ConclusionApheleia‐001 is projected to accelerate clinical trial enrollment and reduce the cost of an early phase therapeutic AD clinical trial. With this approach, initial screen fails will be done more efficiently (e.g., reduced speed and cost) compared to traditional clinical trial approaches. In addition, Apheleia‐001 optimizes sites for randomizations, therefore improving site resource utilization and finances. If scaled, Apheleia‐001 could significantly impact recruitment timelines across multiple studies, reducing the cost and burden of clinical trial recruitment and execution for sponsors, sites, and participants.

Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies

IntroductionBetween 10 and 50% of early-stage lung adenocarcinoma patients experience local or distant recurrence. Histological parameters such as a solid or micropapillary growth pattern are well-described risk factors for recurrence. However, not every patient presenting with such a pattern will develop recurrence. Designing a model which can more accurately predict recurrence on small biopsy samples can aid the stratification of patients for surgery, (neo-)adjuvant therapy, and follow-up. Material and MethodsIn this study, a statistical model on biopsies fed with histological data from early and advanced-stage lung adenocarcinomas was developed to predict recurrence after surgical resection. Additionally, a convolutional neural network (CNN)-based artificial intelligence (AI) classification model, named AI-based Lung Adenocarcinoma Recurrence Predictor (AILARP), was trained to predict recurrence, with an ImageNet pre-trained EfficientNet that was fine-tuned on lung adenocarcinoma biopsies using transfer learning. Both models were validated using the same biopsy dataset to ensure that an accurate comparison was demonstrated. ResultsThe statistical model had an accuracy of 0.49 for all patients when using histology data only. The AI classification model yielded a test accuracy of 0.70 and 0.82 and an area under the curve (AUC) of 0.74 and 0.87 on patch-wise and patient-wise hematoxylin and eosin (H&E) stained whole slide images (WSIs), respectively. ConclusionAI classification outperformed the traditional clinical approach for recurrence prediction on biopsies by a fair margin. The AI classifier may stratify patients according to their recurrence risk, based only on small biopsies. This model warrants validation in a larger lung biopsy cohort.

Assessing progress in managing and improving quality in nascent integrated care systems in England.

In 2022, England embarked on an ambitious reorganisation to produce an integrated health and care system, intended also to maximise population health. The newly created integrated care systems (ICSs) aim to improve quality of care, by achieving the best outcomes for individuals and populations through the provision of evidence-based services. An emerging approach for managing quality in organisations is the Quality Management System (QMS) framework. Using the framework, this study assessed how ICSs are managing and improving quality. Four ICSs were purposively sampled, with the data collected between November 2021 and May 2022. Semi-structured interviews with system leaders (n=60) from health and social care, public health and local representatives were held. We also observed key ICS meetings and reviewed relevant documents. A thematic framework approach based on the QMS framework was used to analyse the data. The ICSs placed an emphasis on population health, reducing inequity and improving access. This represents a shift in focus from the traditional clinical approach to quality. There were tensions between quality assurance and improvement, with concerns that a narrow focus on assurance would impede ICSs from addressing broader quality issues, such as tackling inequalities and unwarranted variation in care and outcomes. Partnerships, a key enabler for integration, was seen as integral to achieving improvements in quality. Overall, the ICSs expressed concerns that any progress made in quality development and in improving population health would be tempered by unprecedented system pressures. It is unclear whether ICSs can achieve their ambition. As they move away from an assurance-dominated model of quality to one that emphasises openness, learning and improvement, they must simultaneously build the digital infrastructure, staff expertise and culture to support such a shift.

Outcomes for Adaptive Mentalization Based Integrative Treatment informed care for adolescents using a deployment-based approach.

Adolescent mentalisation-based integrative therapy (AMBIT) is a whole-systems approach designed to enhance the effectiveness and coordination of care for clients experiencing severe and pervasive difficulties in social and health care settings, who have not responded to traditional clinical approaches. AMBIT is a team-based manualised method that primarily aims to bolster mental state understanding and discourse focused on the client within and between teams. Over 300 teams worldwide have been trained in and adhere to AMBIT principles. In this paper, we review and summarise the outcomes reported by eight AMBIT-informed teams that have published their findings with young people. Each report is discussed, and limitations of the data provided are identified. A synthesis of the findings across the studies suggests a generally positive impact of teams informed by AMBIT with moderate to large effect sizes on reducing symptoms and improving functionality. This study suggests that AMBIT may be a promising approach for young people with multiple problems but further research is needed to identify the active mechanisms of change in complex helping systems.

Enhanced skin burn assessment through transfer learning: a novel framework for human tissue analysis

Visual inspection is the typical way for evaluating burns, due to the rising occurrence of burns globally, visual inspection may not be sufficient to detect skin burns because the severity of burns can vary and some burns may not be immediately apparent to the naked eye. Burns can have catastrophic and incapacitating effects and if they are not treated on time can cause scarring, organ failure, and even death. Burns are a prominent cause of considerable morbidity, but for a variety of reasons, traditional clinical approaches may struggle to effectively predict the severity of burn wounds at an early stage. Since computer-aided diagnosis is growing in popularity, our proposed study tackles the gap in artificial intelligence research, where machine learning has received a lot of attention but transfer learning has received less attention. In this paper, we describe a method that makes use of transfer learning to improve the performance of ML models, showcasing its usefulness in diverse applications. The transfer learning approach estimates the severity of skin burn damage using the image data of skin burns and uses the results to improve future methods. The DL technique consists of a basic CNN and seven distinct transfer learning model types. The photos are separated into those displaying first, second, and third-degree burns as well as those showing healthy skin using a fully connected feed-forward neural network. The results demonstrate that the accuracy of 93.87% for the basic CNN model which is significantly lower, with the VGG-16 model achieving the greatest accuracy at 97.43% and being followed by the DenseNet121 model at 96.66%. The proposed approach based on CNN and transfer learning techniques are tested on datasets from Kaggle 2022 and Maharashtra Institute of Technology open-school medical repository datasets that are clubbed together. The suggested CNN-based approach can assist healthcare professionals in promptly and precisely assessing burn damage, resulting in appropriate therapies and greatly minimising the detrimental effects of burn injuries.

Instrumental assessment of dynamic postural stability in patients with unilateral vestibular hypofunction during straight, curved, and blindfolded gait.

To characterise dynamic postural stability of gait in patients with vestibular hypofunction (PwVH) using a sensor-based assessment while performing dynamic tasks and to correlate the results of this evaluation with clinical scales. This cross-sectional study involved 22 adults between 18 and 70years old from a healthcare hospital centre. Eleven patients suffering from chronic vestibular hypofunction (PwVH) and eleven healthy controls (HC) were evaluated through a combined inertial sensor-based and clinical scale assessment. Participants were equipped with five synchronised inertial measurement units (IMUs) (128Hz, Opal, APDM, Portland, OR, USA): three IMUs were located on the occipital cranium bone, near the lambdoid suture of the head, at the centre of the sternum, and at L4/L5 level, just above the pelvis, and were used to quantify gait quality parameters, while the other two were located slightly above lateral malleoli and used to perform stride and step segmentation. Three different motor tasks were performed in a randomized order: the 10-m Walk Test (10mWT), the Figure of Eight Walk Test (Fo8WT) and the Fukuda Stepping Test (FST). A set of gait quality parameters related to stability, symmetry and smoothness of gait were extracted from IMU data and correlated with the clinical scale scores. PwVH and HC results were compared to test for significant between-group differences. Significant differences were found for the three motor tasks (10mWT, Fo8WT and FST) when comparing PwVH and HC groups. For the 10mWT and the Fo8WT, significant differences between the PwVH and HC groups were found for the stability indexes. Considering the FST, significant differences between the PwVH and HC groups were also found in the stability and symmetry of gait. A significant correlation was found between the Dizziness Handicap Inventory and gait indices during the Fo8WT. In this study, we characterized the dynamic postural stability alterations during linear, curved, and blindfolded walking/stepping in PwVH combining an instrumental IMU-based with traditional clinical scales approach. Combining instrumental and clinical evaluation for dynamic stability of gait alterations in PwVH is useful in thoroughly evaluating the effects of unilateral vestibular hypofunction.

Recent Developments in Tacrine-based Hybrids as a Therapeutic Option for Alzheimer's Disease.

Alzheimer's disease (AD) is a multifactorial, irreversible, and age-related neurodegenerative disorder among the elderly. AD attracts attention due to its complex pathogenesis, morbidity and mortality rates, and the limitations of drugs used in the treatment of AD. Cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists are used in the clinic. While tacrine, donepezil, galantamine, and rivastigmine are cholinesterase inhibitors, memantine is a non-competitive NMDA receptor antagonist. However, these drugs could not delay the progress of AD. The traditional clinical approach which is the one drug-one target concept is not entirely effective in the treatment of AD. Also, it is of high-priority to develop potent and novel anti-AD drugs by the design concept of multitarget directed ligands (MTDLs) which combine pharmacophores interacting with different pathways in AD. This article provides an overview of the noteworthy structural modifications made to tacrine to develop novel candidates for anti-Alzheimer drugs. Due to the complex pathology of AD, multifunctional tacrine-based ligands targeting different hallmarks, β-amyloid, tau protein, N-methyl-Daspartate receptor, cholinesterases, monoamine oxidases, secretases, have been studied. Here, tacrinebased derivatives including heterocyclic structures such as dihydroxypyridine, chromene, coumarin, pyrazole, triazole, tetrahydroquinolone, dipicolylamine, arylisoxazole were reported with promising anti-AD effects compared to tacrine. In vitro and in vivo assays showed that new tacrine-based hybrids, which are selective, neuroprotective, and non-hepatotoxic, might be considered as remarkable anti-AD drug candidates for further clinical studies.

A modular fuzzy expert system for chemotherapy drug dose scheduling

This study presents a modular Fuzzy Expert System (FES) for chemotherapy drug dose scheduling. The computational model considers the patient’s Body Surface Area (BSA) and experts’ opinions to calculate chemo doses following the clinical practice. A proper balance between reducing cancerous cells and toxic side effects is required for effective drug scheduling. Still, in many cases, traditional clinical approaches fail to determine appropriate therapeutical doses that balance all restrictions. In our proposed system, FES-1 is developed to determine primary drug doses based on experts’ opinions and competing treatment objectives. To adjust the dose, FES-2 is developed based on clinical practices, the patient’s BSA, and experts’ opinions. The final chemotherapy drug dose schedule is generated by combining the outputs of FES-1 and FES-2, which is the proposed modular FES. A growth model is used in this work to observe response due to administration of chemotherapy drug doses and to determine the following doses by considering cancer patients’ three weight patterns (increasing, decreasing, and random order). Extensive simulation results and comparative assessment with other current computational chemotherapy drug scheduling models validate the effectiveness and the superiority of the model proposed in this study over the other methods reported in relevant studies.

A Deep Learning Approach for Diabetic Foot Ulcer Classification and Recognition

Diabetic foot ulcer (DFU) is one of the major complications of diabetes and results in the amputation of lower limb if not treated timely and properly. Despite the traditional clinical approaches used in DFU classification, automatic methods based on a deep learning framework show promising results. In this paper, we present several end-to-end CNN-based deep learning architectures, i.e., AlexNet, VGG16/19, GoogLeNet, ResNet50.101, MobileNet, SqueezeNet, and DenseNet, for infection and ischemia categorization using the benchmark dataset DFU2020. We fine-tune the weight to overcome a lack of data and reduce the computational cost. Affine transform techniques are used for the augmentation of input data. The results indicate that the ResNet50 achieves the highest accuracy of 99.49% and 84.76% for Ischaemia and infection, respectively.

ТЕМНА СТОРОНА ІДЕАЛЬНОГО КОХАННЯ: РОМАНТИЧНІ СТОСУНКИ З НАРЦИСОМ

Using traditional clinical approaches and the results of extensive statistical researches of recent years, the author comprehensively analyzed the development and the functioning of a romantic relationship with a narcissist. Love is one of the most popular means providing narcissistic aspirations. Probably, this way is chosen by individuals with the appropriate potential (attractiveness, charm, sexually inviting behavior) to satisfy their own narcissism. It is relatively easy to achieve an idealization from a romantic partner, her/his emotional dependence and power over him/her. Such perspectives create hope for a narcissist to transform his/her life by filling him/herself with the love of the partner, which should compensate childhood emotional traumas and reinforce the narcissist's extremely inflated but fragile self-esteem. Narcissists are extremely successful in the relationship initiation and its initial phase, creating an impression of ideal love. However, they experience significant problems in the later stages of relationship development. They do not want to build a partnership at all, always remain opened to new relationships. When it is no longer possible to increase admiration by his/her partner, they switch to the strategy of rivalry. Through the use of various forms of abuse, exploitation and infidelity, the narcissist strengthens his/her self-esteem, feeling power over his/her partner and her/his emotional dependence. This causes the partner's emotional injuries, who over time also begins to reject and avoid the narcissist. The consequences for the narcissist are: reduced quality of life, low relationship satisfaction and feelings of loneliness. But since narcissism is largely determined genetically, by a history of significant relationships in childhood and provides partially successful adaptation, the prospects for changing the narcissistic style of romantic relationships through psychotherapy are pessimistic. However, psychological help is necessary and effective for a narcissist's romantic partner.

Nanopore sequencing of clonal IGH rearrangements in cell-free DNA as a biomarker for acute lymphoblastic leukemia.

Acute Lymphoblastic Leukemia (ALL) is the most common pediatric cancer, and patients with relapsed ALL have a poor prognosis. Detection of ALL blasts remaining at the end of treatment, or minimal residual disease (MRD), and spread of ALL into the central nervous system (CNS) have prognostic importance in ALL. Current methods to detect MRD and CNS disease in ALL rely on the presence of ALL blasts in patient samples. Cell-free DNA, or small fragments of DNA released by cancer cells into patient biofluids, has emerged as a robust and sensitive biomarker to assess cancer burden, although cfDNA analysis has not previously been applied to ALL. We present a simple and rapid workflow based on NanoporeMinION sequencing of PCR amplified B cell-specific rearrangement of the (IGH) locus in cfDNA from B-ALL patient samples. A cohort of 5 pediatric B-ALL patient samples was chosen for the study based on the MRD and CNS disease status. Quantitation of IGH-variable sequences in cfDNA allowed us to detect clonal heterogeneity and track the response of individual B-ALL clones throughout treatment. cfDNA was detected in patient biofluids with clinical diagnoses of MRD and CNS disease, and leukemic clones could be detected even when diagnostic cell-count thresholds for MRD were not met. These data suggest that cfDNA assays may be useful in detecting the presence of ALL in the patient, even when blasts are not physically present in the biofluid sample. The Nanopore IGH detection workflow to monitor cell-free DNA is a simple, rapid, and inexpensive assay that may ultimately serve as a valuable complement to traditional clinical diagnostic approaches for ALL.

Mesoporous nanoplatform integrating photothermal effect and enhanced drug delivery to treat breast cancer bone metastasis.

Bone metastatic breast cancer has severely threatened the survival and life quality of patients. Due to the suboptimal efficacy of anti-metastatic chemotherapeutic drugs and the complicated bone marrow microenvironments, effective treatment of metastatic breast cancer remains challenging for traditional clinical approaches. In this work, we developed a mesoporous nanoplatform (m-CuS-PEG) with the co-loading of CuS nanodots and a chemotherapeutic drug cisplatin for the combined photothermal-chemotherapy of bone-metastasized breast cancer. The CuS nanodots were decorated onto mesoporous silica (m-SiO2) surface with dendritic mesoporous channels, into which the cisplatin was accommodated. The carboxyl-terminated poly (ethylene glycol) (PEG) was further functionalized onto the surface to obtain the functional nanoplatform m-CuS-PEG. The drug release of the loaded cisplatin exhibited pH- and thermal-dual responsive manner. The attached CuS nanodots rendered the mesoporous nanoplatform with high photothermal conversion ability. Upon irradiation with a near-infrared laser in the second near-infrared (NIR-II) window, m-CuS-PEG dispersions exhibited rapid temperature elevation and high photostability. The results revealed that m-CuS-PEG had excellent biocompatibility. The cisplatin-loaded m-CuS-PEG not only showed superior cancer cell-killing effects, but also significantly inhibit the growth of metastatic tumors. The tumor-induced bone destruction was also dramatically attenuated by the mesoporous nanoplatform-mediated combined therapy. Overall, the developed functional nanoplatform integrates photothermal therapy and efficient chemotherapeutic drug delivery to offer an alternative approach for combating breast cancer bone metastasis.

THE CURRENT ROLE OF MULTIPARAMETRIC MRI IN THE DIAGNOSIS OF PROSTATE CANCER:&#x0D; A LITERATURE REVIEW

Relevance: Multiparametric MRI (mpMRI) is one of the main methods for diagnosing prostate cancer (PCa). Although mpMRI has been adopted into routine urological and oncological practice in a few short years, there are conflicting views on the timing of mpMRI.&#x0D; The purpose was to study the diagnostic value and role of mpMRI at the stages of diagnosis of prostate cancer.&#x0D; Methods: The article reviews the literature on the use of mpMRI in diagnosing prostate cancer in the framework of traditional clinical approaches.&#x0D; Results: current national guidelines in Europe emphasize the value of mpMRI in diagnosing patients with suspected PCa. The rationale for&#x0D; using mpMRI in selecting patients with suspected PCa who should and should not be biopsied and selecting areas of the prostate for biopsy is&#x0D; compelling. The evidence base, including level 1 studies, is overwhelming, as are arguments for patient benefit in avoiding biopsy or overdiagnosis&#x0D; of clinically insignificant cancer.&#x0D; Conclusion: Patients considering biopsy start to realize that mpMRI imaging can avoid biopsy in some cases and make it more targeted in&#x0D; others. For obvious reasons, these patients will seek to avoid the risk of biopsy or minimize the risk with fewer biopsy specimens. Switching from&#x0D; “standard” SB to TB judiciously and selectively augmented with BD using a two-stage risk assessment offers the best compromise to reduce biopsy&#x0D; rates and reduce overdiagnosis of cnPCa while minimizing the chances of missing clinically significant cancer. Evidence that it is possible to avoid&#x0D; SB altogether, even in the era of mpMRI before biopsy, is weak. This provides grounds for searching for new methods for diagnosing clinically&#x0D; significant cancer using mpMRI

Listening to the silent struggles of bipolar disorder through sonification of iMoodJournal data.

Listening to the silent struggles of bipolar disorder through sonification of iMoodJournal data.

Clinical Application of Artificial Intelligence: Auto-Discerning the Effectiveness of Lidocaine Concentration Levels in Osteosarcoma Femoral Tumor Segment Resection.

Adolescents and children worldwide are threatened by osteosarcoma, a tumor that predominantly affects the long bone epiphysis. Osteosarcoma is the most common and highly malignant bone tumor in youngsters. Early tumor detection is the key to effective treatment of this disease. The discovery of biomarkers and the growing understanding of molecules and their complex interactions have improved the outcome of clinical trials in osteosarcoma. This article describes biomarkers of osteosarcoma with the aim of positively influencing the progress of clinical treatment of osteosarcoma. Femoral bone tumor is a typical condition of osteosarcoma. Due to the wide range of femoral stem types, complexities in the distal femur, and tumors in the rotor part of femur, physicians following the traditional clinical approach face difficulties in removing the lesion and fixing the femur with resection of the tumor segment. In this paper, the effect of small doses of different concentrations of lidocaine anesthesia in patients undergoing lumpectomy for osteosarcoma femoral tumor segments is investigated. A computer-based artificial intelligence method for automated determination of different concentration levels of lidocaine anesthesia and amputation of osteosarcoma femoral tumor segment is proposed. Statistical analysis is carried on the empirical data including intraoperative bleeding, intraoperative and postoperative pain scores, surgical operation time, postoperative complications, patient satisfaction, and local anesthetic dose. The results showed that the patients in the study group had low intraoperative bleeding, short operation time, low postoperative hematoma formation rate, high patient satisfaction, higher dosage of anesthetic solution, and low dosage of lidocaine. Results revealed that mean arterial pressure and heart rate in extubating and intubating were significantly lower in the observation group than in the control group, and a significant difference (P < 0.05) was observed between the two groups. This proves that the proposed algorithm can adequately reduce bleeding, alleviate postoperative pain, shorten operation time, reduce complications, accelerate recovery, and ensure better treatment results.

The Potential Impact of Adjunct Digital Tools and Technology to Help Distressed and Suicidal Men: An Integrative Review.

Suicidal men feel the need to be self-reliant and that they cannot find another way out of relationship or socioeconomic issues. Suicide prevention is of crucial importance worldwide. The much higher rate of suicide in men engenders action. The prelude is a subjective experience that can be very isolating and severely distressing. Men may not realize a change in their thinking and behaviors, which makes it more difficult to seek and get help, thereby interrupting a “downward spiral”. Stoicism often prevents men from admitting to their personal struggle. The lack of “quality” connections and “non-tailored” therapies has led to a high number of men “walking out” on traditional clinical approaches. But there are complicated relationships in motivations and formative behaviors of suicide with regards to emotional state, psychiatric disorders, interpersonal life events and suicidal behavior method selection. Middle-aged and older men have alternated as the most at-risk of suicide. There is no one solution that applies to all men, but digital tools may be of assistance (e.g., video conferences, social networks, telephone calls, and emails). Digital interventions require higher levels of effectiveness for distress and suicidality but self-guided approaches may be the most suitable for men especially where linked with an integrated online suicide prevention platform (e.g., quick response with online chats, phone calls, and emails). Furthermore, technology-enabled models of care offer promise to advance appropriate linking to mental health services through better and faster understanding of the specific needs of individuals (e.g., socio-cultural) and the type and level of suicidality experienced. Long-term evidence for suicidality and its evaluation may benefit from progressing human computer-interaction and providing impetus for an eminent integrated digital platform.