Limited Number Research Articles

The application of MD simulation to lead identification, vaccine design, and structural studies in combat against leishmaniasis - A review.

Drug discovery, vaccine design, and protein interaction studies are rapidly moving toward the routine use of molecular dynamics simulations (MDS) and related methods. As a result of MDS, it is possible to gain insights into the dynamics and function of identified drug targets, antibody-antigen interactions, potential vaccine candidates, intrinsically disordered proteins, and essential proteins. The MDS appears to be used in all possible ways in combating diseases such as cancer, however, it has not been well documented as to how effectively it is applied to infectious diseases such as Leishmaniasis. As a result, this systematic review aims to survey the application of MDS in combating leishmaniasis. We have systematically collected articles that illustrate the implementation of MDS in drug discovery, vaccine development, and structural studies related to Leishmaniasis. Of all the articles reviewed, we identified that only a limited number of studies focused on the development of vaccines against Leishmaniasis through MDS. Also, the PCA and FEL studies were not carried out in most of the studies. These two were globally accepted utilities to understand the conformational changes and hence it is recommended that this analysis should be taken up in similar approaches in the future.

Finding out the “gender” sooner: Ethical tensions and parental motivation in discovering fetal sex and chromosomal anomaly risk using noninvasive prenatal testing (NIPT)

Noninvasive prenatal testing (NIPT) has rapidly expanded in both utilization and scope since it became available in 2011. While NIPT screens for a limited number of chromosomal anomalies, it has become colloquially known as the “gender” test because of the ability to determine sex chromosome information. Yet users often report being less interested in learning about fetal risk for sex chromosome anomalies (SCAs). To date, most research with NIPT users has focused on those who receive “high risk” or “positive” results. Yet most NIPT users will receive “low risk” results. This is significant because NIPT continues to grow in popularity. To better understand how NIPT “test-negative” users report testing motivations, we analyzed semi-structured interviews with 37 NIPT users using constructivist grounded theory. Participants reported two motivations in using NIPT: 1) learning fetal sex information and 2) gaining “peace of mind” in confirming low risk of chromosomal anomaly, or disability. However, these motivations were also in tension with each other as users described gaining fetal sex information as a valued benefit that offset any anxiety or fear they experienced from participating in NIPT. These findings have implications for ongoing ethical debates over the role of fetal sex determination in NIPT and suggest that NIPT may also raise more subtle ethical challenges including the reinforcement of sex and gender binaries and the foreclosure of disability as familial possibility, revealing how epistemic shortcuts are at play within NIPT.

Automatically Temporal Labeled Data Generation Using Positional Lexicon Expansion for Focus Time Estimation of News Articles

Many facts change over time, which is a fundamental aspect of our physical environment. In the case of pandemic articles, the user is not interested in the creation date of the document but in the facts and the cause of the last pandemic. Fake news can be better combated by having a document with a temporal focus. Currently, neither the sequence of events nor the temporal focus is considered when obtaining news documents. Despite the limited number of temporal aspects in the available datasets, it is difficult to test and evaluate the temporal conclusions of the model. The goal of this work is to develop a temporal focus news article retrieval model based on co-training to advance research in semi-supervised learning. A mapping of the dataset is performed using (1) the evolving focus time of news articles and (2) the semi-supervised method based on coincidence contexts for learning low-dimensional continuous vectors for learning neural contrast embedding models generating focus time-based query in sequential news articles to facilitate temporal understanding by learning low-dimensional continuous vectors. A diverse dataset of news articles is used to evaluate the effectiveness of the proposed method. With semi-supervised learning and lexicon expansion, the result of the developed model can achieve 89%. The method performed better than previous baselines and traditional machine learning models with improvements of 12.65% and 4.7%, respectively.

K-space holographic multiplexing for synthetic aperture diffraction tomography

Optical diffraction tomography can be performed with low phototoxicity and photobleaching to analyze 3D cells and tissues. It is desired to develop high throughput and powerful data processing capabilities. We propose high bandwidth holographic microscopy (HBHM). Based on the analyticity of complex amplitudes, the unified holographic multiplexing transfer function is established. A high bandwidth scattering field is achieved via the k-space optical origami of two 2D wavefronts from one interferogram. Scanning illumination modulates the high-horizontal and axial k-space to endow synthetic-aperture from 2D high space-bandwidth product (SBP) scattering fields. The bright-field counterpart SBP of a single scattering field from HBHM is 14.6 megapixels, while the number of pixels is only 13.7 megapixels. It achieves an eight-fold SBP enhancement under the same number of pixels and diffraction limit. The HBHM paves the way toward the performance of high throughput, large-scale, and non-invasive histopathology, cell biology, and industrial inspection.

The Efficacy and Safety of Inetetamab and Pyrotinib in Combination with Vinorelbine for Second-line Therapy and Beyond in HER2-positive Metastatic Breast Cancer: A Single-institution Clinical Experience.

This study aimed to observe the efficacy and safety of inetetamab and pyrotinib in combination with vinorelbine in second-line therapy and beyond in HER2-positive metastatic breast cancer (MBC). Patients with HER2-positive MBC admitted to our hospital from January 2016 to December 2021 were selected. For patients who could not receive antibody‒drug conjugates (ADCs) during second-line (2nd-line) or third-line and beyond (≥3rd-line) anti-HER2 therapy, inetetamab + pyrotinib + vinorelbine was used for treatment until unacceptable adverse events occurred or the disease progressed, as evaluated by the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 every 2 cycles. The progression-free survival (PFS), objective response rate (ORR), clinical benefit rate (CBR), and adverse reactions were recorded. Multivariate Cox regression analysis was performed to explore the prognostic factors influencing the curative effect. Overall, 52 patients were included; 13 patients received 2nd-line treatment, and 39 patients received ≥3rd-line treatment. The median PFS (mPFS) for all patients treated with inetetamab + pyrotinib + vinorelbine was 7 months. The mPFS of the 2nd-line subgroup was significantly better than that of the ≥3rd-line subgroup (17 vs. 5 months, P = 0.001). The mPFS of the subgroups that received trastuzumab (H) or trastuzumab and pertuzumab (HP) only was significantly better than that of the H or HP and tyrosine kinase inhibitor (TKI) subgroups (8 vs. 5 months, P = 0.030). The mPFS of the HER2 resistance subgroup was better than that of the HER2 refractoriness subgroup (14 vs. 7 months, P = 0.025). Cox regression analysis showed that the treatment line (2nd-line more so than ≥3rd-line) was an independent prognostic factor for PFS. In addition, the ORR and CBR of 2nd-line patients were significantly higher than those of ≥3rd-line patients (69.2% vs. 30.8% and 92.3% vs. 64.1%, respectively). The most common hematological toxicities were leukopenia and neutropenia, and the most common nonhematological toxicity was diarrhea. Inetetamab and pyrotinib in combination with vinorelbine have good efficacy in ≥2ndline treatment of HER2-positive MBC with controllable toxicity, and the combination is a new treatment option, especially for patients who cannot use ADCs in 2nd-line treatment.

Cross-Correlation of Confocal Images for Excised Breast Tissues of Total Mastectomy.

The purpose of this study is to develop an image artifact removal method for radar-based microwave breast imaging and demonstrates the detectability on excised breast tissues of total mastectomy. A cross-correlation method was proposed and measurements were conducted. A hand-held radar-based breast cancer detector was utilized to measure a breast at different orientations. Images were generated by multiplying the confocal image data from two scans after cross-correlation. The optimum reconstruction permittivity values were extracted by the local maxima of the confocal image intensity as a function of reconstruction permittivity. With the proposed cross-correlation method, the contrast of the imaging result was enhanced and the clutters were removed. The proposed method was applied to 50 cases of excised breast tissues and the detection sensitivity of 72% was achieved. With the limited number of samples, the dependency of detection sensitivity on the breast size, breast density, and tumor size were examined. The detection sensitivity was strongly influenced by the breast density. The sensitivity was high for fatty breasts, whereas the sensitivity was low for heterogeneously dense breasts. In addition, it was observed that the sensitivity was high for extremely dense breast. This is the first detailed report on the excised breast tissues.

Outpatient prescription drug interactions at a city-affiliated healthcare center in Vietnam

Context: Adverse drug interactions increase the risk of hospitalization, treatment costs, unfavorable treatment outcomes, and prolonged hospital stays. However, there are a limited number of studies conducted in city-affiliated healthcare settings in Vietnam. Aims: To identify drug interactions in outpatient treatment prescriptions at a city-based healthcare center in the southern region of Vietnam. Methods: A cross-sectional descriptive study was conducted on outpatient treatment prescriptions stored in the outpatient department of a city-affiliated healthcare center from January to June, 2023. The study used two databases for drug interaction checking: the Drug Interactions Checker and Medscape Interactions Checker. Univariate and multivariate regression analyses were used to identify predictors of clinically significant drug interactions. Results: Among 1203 surveyed prescriptions, 36.7% contained at least one clinically-significant drug interaction, with 3% of prescriptions having severe interactions. The highest frequency of drug interactions involved amlodipine and metformin (9.9%). Patients with five or more prescribed medications (OR = 3.305; 95% CI: 2.320-4.708), hypertension (OR = 7.142; 95% CI: 4.658-10.950), dyslipidemia (OR = 2.242; 95% CI: 1.665-3.020), and non-insulin-dependent diabetes (OR = 2.447; 95% CI: 1.817-3.295) had a higher likelihood of experiencing clinically significant drug interactions. Conclusions: This study revealed that over one-third of outpatient prescriptions were associated with clinically-significant drug interactions. This study highlights the importance of clinical pharmacists screening prescriptions to detect and reduce interactions, as well as the application of computerized alert systems with intelligent screening software to minimize drug interactions.

Designing Privacy-Aware IoT Applications for Unregulated Domains

Internet of Things (IoT) applications (apps) are challenging to design because of the heterogeneous systems on which they are deployed. IoT devices and apps may collect and analyse sensitive personal data, which is often protected by data privacy laws, some within highly regulated domains such as healthcare. Privacy-by-design (PbD) schemes can be used by developers to consider data privacy at the design stage. However, software developers are not widely adopting these approaches due to difficulties in understanding and interpreting them. There are currently a limited number of tools available for developers to use in this context. We believe that a successful PbD tool should be able to (i) assist developers in addressing privacy requirements in less regulated domains, as well as (ii) help them learn about privacy as they use the tool. The findings of two controlled lab studies are presented, involving 42 developers. We discuss how such a PbD tool can help novice IoT developers comply with privacy laws (e.g., GDPR) and follow privacy guidelines (e.g., privacy patterns). Based on our findings, such tools can help raise awareness of data privacy requirements at design. This increases the likelihood that subsequent designs will be more aware of data privacy requirements.

TCP-RBA: Semi-supervised learning for traditional chinese painting classification with random brushwork augment

Traditional Chinese painting (TCP), culturally significant, reflects China’s rich history and aesthetics. In recent years, TCP classification has shown impressive performance, but obtaining accurate annotations for these tasks is time-consuming and expensive, involving professional art experts. To address this challenge, we present a semi-supervised learning (SSL) method for traditional painting classification, achieving exceptional results even with a limited number of labels. To improve global representation learning, we employ the self-attention-based MobileVit model as the backbone network. Furthermore, We present a data augmentation strategy, Random Brushwork Augment (RBA), which integrates brushwork to enhance the performance. Comparative experiments confirm the effectiveness of TCP-RBA in Chinese painting classification, demonstrating outstanding accuracy of 88.27% on the test dataset, even with only 10 labels, each representing a single class.

Use of 3D printing to integrate microchip electrophoresis with amperometric detection.

This paper describes the use of PolyJet 3D printing to fabricate microchip electrophoresis devices with integrated microwire electrodes for amperometric detection. The fabrication process involves 3D printing of two separate pieces, a channel layer and an electrode layer. The channel layer is created by 3D printing on a pre-fabricated mold with a T-intersection. For the electrode layer, a stencil design is printed directly on the printing tray and covered with a piece of transparent glass. Microwire electrodes are adhered over the glass piece (guided by underlaying stencil) and a CAD design of the electrode layer is then printed on top of the microwire electrode. After delamination from the glass after printing, the microwire is embedded in the printed piece, with the stencil design ensuring that alignment and positioning of the electrode is reproducible for each print. After a thermal bonding step between the channel layer and electrode layer, a complete electrophoresis device with integrated microelectrodes for amperometric detection results. It is shown that this approach enables different microwire electrodes (gold or platinum) and sizes (100 or 50µm) to be integrated in an end-channel configuration with no gap between the electrode and the separation channel. These devices were used to separate a mixture of catecholamines and the effect of separation voltage on the potential voltage applied on the working electrode was also investigated. In addition, the effect of electrode size on the number of theoretical plates and limit of detection was studied. Finally, a device that contains different channel heights and a detection electrode was 3D-printed to integrate continuous flow sampling with microchip electrophoresis and amperometric detection.

Abstract LB106: Ultra-short ctDNA: A new paradigm for ctDNA liquid biopsy

Abstract Mononucleosomal ctDNA (mnctDNA, 157-bp, double-stranded) spearheads liquid biopsy (LB) for cancer detection, treatment and clinical care. The bottleneck of mnctDNA LB are low copy number of ctDNA and limit of detection of platform technologies. Recent discovery of ultra-short ctDNA (usctDNA, 52-54 nt, single-stranded) that harbors somatic mutations prompted us to explore the quantification and stoichiometry of usctDNA to mnctDNA in plasma and saliva of NSCLC patients. Paired plasma and saliva from 20 advanced NSCLC patients with tissue genotyped positive for L858R were processed for cfDNA extraction and quantification with Qubit and Tape Station. Digital PCR assays targeting L858R somatic mutation to generate amplicons of 57-bp (usctDNA) and 100-bp (mnctDNA) were performed by UCLA and independently by NIST. Results in Table 1 revealed that three findings of usctDNA that will have potential to impact ctDNA liquid biopsy. First, the somatic mutation (L858R) is present in usctDNA. Second, The stoichiometric ratio of usctDNA to mnctDNA is similar in plasma and saliva at 1.6X. For the wild-type counterpart, the ratio is 1.1X for plasma and 0.6X for saliva. Third, the copy number of usctDNA and mnctDNA in saliva to plasma is 7.8X and 7.7X. Conclusion: Detection of tumor-associated/specific EGFR L858R somatic mutations in uscfDNA is translationally impactful, adding 1.6X of the ctDNA targets for molecular detection, effectively cumulating 2.6X of total ctDNA targets, permitting earlier cancer detection, treatment monitoring and therapy prognostication. The finding that saliva harbors 7X of the us- and mnctDNA further raises the prospect of advancing saliva ctDNA liquid biopsy for NSCLC detection as it may effectively allow 15.5X (7.8X+7.7X) ability to detect malignancy-associated ctDNA. Table 1. Quantification of usctDNA and mnctDNA in Plasma and Saliva Mut usctDNA (L858R) WT cfDNA usctDNA mnctDNA U/M uscfDNA mncfDNA U/M Plasma 1555 ± 326 964 ± 209 1.6X 15201 ± 1509 13261 ± 1424 Saliva 12158 ± 1731 7442 ± 1020 1.6X 340896 ± 27170 601733 ± 71573 1.1X Saliva/Plasma (fold X) 7.8 7.7 1.6X 22.4 45.3 0.6X Citation Format: Feng Li, Fang Wei, Hua-Jun He, Chien-Chung Lin, Szu-Chun Yang, Allen Wei-Lun Huang, Cheuk Ying Tang, Yong Kim, David T. Wong. Ultra-short ctDNA: A new paradigm for ctDNA liquid biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB106.

Evaluation of three protocols for direct susceptibility testing for Gram-negative rods from flagged positive blood culture bottles.

Bloodstream infections are associated with high mortality that can be reduced by targeted antibiotic therapy in the early stages of infection. Direct antibiotic susceptibility testing (AST) from flagged positive blood cultures may facilitate the administration of early effective antimicrobials much before the routine AST. Clinical and Laboratory Standards Institute-recommended direct AST can be performed with a limited number of antibiotic disks only. On the other hand, using an automated system for direct AST will not only allow effective laboratory workflow with reduced turnaround time but also provide the minimum inhibitory concentration values of tested antibiotics. However, using expensive automated systems for direct AST may not be feasible for resource-limited laboratories. Therefore, in this study, we aimed to evaluate the CLSI-recommended method and two other direct AST protocols (one with an automated system and the other with disk diffusion) for Gram-negative rods from flagged positive blood cultures.

Measuring Color Index of Transformer Oil–Enabling Single-Wavelength Spectroscopy With Artificial Neural Network-Fuzzy Logic Model

Conventionally, the color index of transformer oil is determined by a color comparator based on the American Society for Testing and Materials (ASTM) D 1500 standard. The equipment requires humans to operate, which leads to human error and limited number of samples tested per day. This work proposes the utilization of single-wavelength spectroscopy with 405 nm laser diode using artificial neural network (ANN) to determine the color index of transformer oil. Two ANN models were developed using data collected from 50 oil samples with different optical pathlengths of 1 to 10 mm, and laser output powers of 1 to 15 mW. The first model classified the input into different color indices and another model correlated the input parameters through regression analysis to determine the color index. A hybrid ANN-fuzzy logic model was also developed to improve the color index prediction. The root-mean-squared error (RMSE) obtained from the prediction by ANN regressor and ANN classifier are 0.5602 and 0.6416, respectively. The hybrid ANN-fuzzy logic model improves the RMSE especially for optical pathlengths <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula> 5 mm, which is required for measuring samples with high color index. This proposed method reduces the dependency on complex optoelectronic hardware to obtain highly accurate results. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Unlike the conventional testing method for color index of transformer oil that requires human observation, the findings of this study enables the possibility of compact and smart portable device through the utilization of single wavelength spectroscopy with machine learning models. With no human involvement, more computational power with lesser hardware dependency, the maintenance cost and error can be reduced. This proposed method can potentially be applied to measure the color of other amber-colored liquid products such as olive oil, honey and others.

A Clustering-Based Optimization Approach for Hospital Miscoding Correction

This paper addresses the problem of correcting medical coding errors with respect to some coding recommendations. The problem consists in clustering medical codings and determining for each cluster the set of features to correct in order to maximize the financial benefits subject to coding correction effort constraints. For this purpose, we model the coding recommendation as a disjunction of hypercubes and introduce the concept of correction sets. A mixed integer linear programming model is then proposed to assign medical codes to correction sets in order to maximize the financial benefits. The miscoding is then explained by characterizing optimal clusters with association rules and coding error distribution. A case study on patient stays associated with malnutrition-related ICD codes is presented, and the performance of the proposed methodology is assessed in regard to the current coding staff practice. A significant increase in health services reimbursement is achieved with a limited number of subjects’ features reviewed. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Medical miscoding has a significant negative impact on hospitals with a financial loss for under coding and a penalty for over coding. Whether a medical review is necessary for all descriptive features of a miscoded subject? Is it possible to reduce unnecessary medical reviews without compromising the goal of increasing hospital financial benefits? This article attempts to answer these questions with a data-driven optimization approach to determine a limited number of miscoding clusters and the set of features to review for each in order to best balance the financial benefits and the medical review workload. The application to a real-life case study leads to a significant increase in hospital fiscal revenue of nearly 6,992,489.69, while reviewing only a small number of descriptive features (5293 out of 22056 features, or 24% of features). Causes are also provided for each discovered coding error subtype to ameliorate medical coders’ coding practices. Furthermore, the proposed approach allows the decision-maker to balance the cost-benefit and the requirement of public health institutions (i.e., miscoding rate).

Prognostic implications of MXRA8 expression in colorectal cancer and its role in tumor progression

Matrix Remodeling Associated 8 (MXRA8) is a type I transmembrane protein capable of modulating integrin signaling and regulating cell-cell interactions, and also functions as a receptor for multiple arthritogenic alphaviruses. Although limited numbers of studies have provided evidence indicating a potential role of MXRA8 in different types of cancer, the potential contrubition of MXRA8 in colorectal cancer (CRC) has not yet been fully elucidated. Therefore, our aim was to conduct a comprehensive analysis elucidating the prognostic value of MXRA8 in CRC. The results revealed that MXRA8 was highly expressed in CRC compared to normal tissue. Notably, there was a substantial correlation with the TNM stage, and elevated MXRA8 expression was indicative of a poorer prognosis in CRC cases. Furthermore, co-expression analysis indicated that MXRA8 is predominantly involved in hypoxia and epithelial-mesenchymal transition pathway. In conclusion, this study demonstrates the potential roles of MXRA8 in predicting CRC prognosis and contributes to the elucidation of how MXRA8 might be involved in the mechanisms underlying CRC carcinogenesis.

Current Status of Potential Antiviral Drugs Derived from Plant, Marine, and Microbial Sources

Abstract: Natural substances have been the principal source of medications since antiquity. Natural goods are gaining popularity as a source of novel medications. This article investigates a variety of variables like plant, marine, and microbial sources that contribute to the growing interest in natural goods as a source of novel medications. Viruses have remained resistant to treatment and prevention for a longer period than other forms of life. Viral diseases can currently only be treated with a limited number of drugs. Significant research initiatives have been committed to identifying novel antiviral natural compounds to fight viruses that harm people, plants, insects, animals, fungi, and microbes. A recent study of the prevalence and sources of antiviral medications licensed by the Food and Drug Administration (FDA) has focused on natural products. Out of the estimated 250,000 higher plant species, only 5 to 15 percent have been thoroughly evaluated for the existence of bioactive substances in them, and the ability of the other species has hardly been investigated. This review aims to offer an overview of the crucial role played by natural products in the discovery and development of novel antiviral drugs with potent antiviral activity, including phytochemicals such as carbohydrates, coumarins, flavonoids, chromones, alkaloids, lignans, phenols, tannins, proteins, peptides, antiviral plant extracts, other marine, and microbial sources.

Human-robot collaborative disassembly enabled by brainwaves and improved generative adversarial network

Human-robot collaboration (HRC) can greatly facilitate the disassembling processes of end-of-life (EoL) products. For the robot in HRC, an intuitive control function enabled by a brain-machine interface (BMI) and human brainwaves will be useful to support dynamic decision-making under various disassembly conditions. However, a major challenge in developing a BMI-enabled HRC disassembly system is that there are usually a limited number of brainwave signals available for system training. To address the challenge, a novel model, namely TCN-D2GAN, was designed in this study. The model was used to augment acquired brainwave signals and support the establishment of the BMI-enabled HRC disassembly system. The innovations of the TCN-D2GAN model come from the following aspects: (i) the strengths of a temporal convolutional network (TCN) and a dual discrimination generative adversarial network (D2GAN) were combined to accomplish high-performance signal augmentation, and (ii) new loss functions were defined in the model to avoid the use of hyperparameters, so the training effect of the model can be optimised. Based on two public electroencephalography (EEG) datasets, experiments for signal augmentation and system training were carried out. The TCN-D2GAN model was compared with several mainstream generative adversarial network (GAN) models. Results indicated that the TCN-D2GAN model exhibited better performance in terms of signal classification accuracy and training efficiency. Finally, disassembly experiments were presented to validate the applicability of the system.

Current genetic defects in common variable immunodeficiency patients on the geography between Europe and Asia: a single-center experience.

Identification of the causes of monogenetic common variable immunodeficiency (CVID) patients has rapidly increased in the last years by means of worldwide availability of appropriate genetic diagnostic methods. However, up to date, very limited numbers of reports demonstrating the role of geography, ethnicity, and consanguinity have been published. Here, we reported the first study of Turkish CVID patients and compared them with the results of three countries from America, Europe, and Asia. A total of 100 children diagnosed as CVID according to the criteria of European Society for Immunodeficiencies were enrolled, and they were genetically analyzed by using targeted next-generation sequencing and whole-exome sequencing. The median age of our patients was 5.8years (range, 3.0-16.0years) at clinical diagnosis and 9.0years (range, 4.8-21.0years) at the time of genetic diagnosis. The consanguinity rate was 24%. Disease-causing pathogenic variants were defined in 40% of patients in a total of 17 different genes. Sixteen of 40 identified pathogenic variants were novel (40%). We determined 18 surface molecular defects, 10 cytosolic defects, 9 nuclear defects, and 3 others. In our cohort, the most common gene was TACI (15/40 in pathogenic variant identified cases and 15/100 in all cases) followed by the others such as PLCү2, LRBA, TCF3, and STAT1. In contrast to our expectations, our results were more similar to American and European population rather than Asians, although we also have high consanguinity rates and live on the geography between Europe and Asia. Genetic investigation is a great challenge, because of the complexity and heterogeneity of the disease, and each country has to know their own current genetic landscape in CVID for a better and successful management of the patients.

Gaslighting ve Kişilerarası İlişkiler: Sistematik Derleme Çalışması

Gaslighting is a manipulation technique that makes the perpetrator doubt the mind of the victim, questions the perception of reality, and makes the person think that they are crazy. Although gaslighting is thought to be a marriage syndrome, gaslighting can occur not only in marriages but also in all relationships. The purpose of this review study is to systematically compile the studies on gaslighting and relationships, to reveal what kind of relationships gaslighting is seen and what its outputs are. Scopus, PubMed, Cochrane Library, TRDizin, and Web of Science databases were used in the research. The systematic review was carried out according to the PRISMA criteria. The terms "gaslighting", "gaslight" and "relationship" were used as keywords in Turkish and English to be scanned in databases. 97 studies were accessed from the databases, 31 studies were viewed and 17 of them were included in the study. Most of the studies were conducted in the USA. The study findings showed that gaslighting can occur in many different areas such as health, politics, and romantic and social relationships. It has been seen that the personality of the victim and the perpetrator, partner addiction, and the balance of power in the relationship are the factors that affect gaslighting. In addition, it has been found in the literature that there are a very limited number of studies on gaslighting. Especially in Turkish literature, quantitative or qualitative study findings directly addressing people who have been exposed to gaslighting have not been found. The reason for this was thought to be related to the fact that a scale study on gaslighting has not yet been carried out in Turkiye.

Функционально-трудоемкостный анализ кадровых процессов системы менеджмента качества организации

The article discusses an approach to improving personnel (supporting) processes in the organisation’s quality management system based on the methodology tool modification of the functional-cost analysis (FCA) and the qualimetric substantiation of critical indicators of the studied process function parameters. The paper analyses tools and technologies for structuring, correcting, and improving personnel processes in the organization’s quality management system as well as problems associated with their application in practice. The expediency for operational determination of the direction for improving the personnel process quality is substantiated by studying a limited number of their parameters. Importance (significance) and labour intensity of personnel process functions are considered as the studied parameters. A procedure for functional and labour-intensive analysis (FLIA) is proposed, which is the personnel process improvement based on analysing the importance-labour intensity ratio of function implementation, allowing the process owner to quickly obtain information about the process state. The procedure of functional and labour-intensive analysis is considered through the approbation on the example of the personnel process “Personnel Recruitment.” Critical indicators of “Personnel Recruitment” structure are compared with similar indicators obtained based on applying functional-cost analysis to the process under consideration. The article argues for the promising use of the proposed procedure for enhancing the personnel processes of the organization’s quality management system, aimed at identifying the direction for their improvement.