Metabolic Obesity in People with Normal Body Weight (MONW)—Review of Diagnostic Criteria

Disorders of metabolic obesity with normal body weight (MONW) are widely recognized risk factors for the development of cardiovascular diseases and type 2 diabetes. Despite this, MONW is not diagnosed in clinical practice. There is no consensus on the definition of MONW, and measuring the degree of insulin resistance or obesity among apparently healthy, non-obese patients is not widely applicable. The awareness of the relationship between metabolic disorders such as MONW and a higher risk of mortality from cardiovascular causes and other related diseases prompts the need for action to be taken aimed at creating appropriate diagnostic models that will allow for the effective detection of those with metabolic abnormalities among people with normal body weight. Such actions are decisive in the prevention and treatment of diseases. Therefore, the purpose of this article is to review the MONW diagnostic criteria used over the years.

SAA4 is a Diagnostic Marker to Enhance Detection Forrheumatoid Arthritis Combined with Anti-CCP

Objective Serum amyloid A4 (SAA4) is an apolipoprotein that is associated with high-density lipoprotein (HDL) in plasma. In this present investigation, we appraised the potential of SAA4 as a novel diagnostic biomarker for rheumatoid arthritis (RA) combined with other established RA biomarkers, including anticitrullinated protein antibody (anti-CCP), rheumatoid factor (RF)，and C-reactive protein (CRP). Based on the correlative measures of the biomarkers, we developed a diagnostic model of RA by integrating serum levels of SAA4 with these clinical parameters. Methods A number of 316 patients were recruited in the current research. The serum levels of SAA4 were assessed by quantitative ELISA. The specificity and sensitivity of biomarkers were evaluated by using a receiver-operator curve (ROC) analysis to determine their diagnostic efficiency. Univariate and multivariate logistic regression analyses were used to screen and construct the diagnostic models for RA , consisting of diagnostic biomarkers and clinical data. A diagnostic nomogram was then generated based on logistic regression analysis results. Results The serum levels of SAA4 were considerably greatest in RA patients in comparison to other control subjects (P<0.001). Compared with anti-CCP, RF and CRP respectively, SAA4 had the highest specificity (88.60%) for diagnosing RA. The combination of SAA4 with anti-CCP could have the highest diagnostic accuracy when paired together, with highest sensitivity (91.14%) in parallel and highest specificity(98.10) in series. We successfully developed two diagnostic models: the combined model of SAA4 and anti-CCP (model A), and the combined model of SAA4, CRP, anti-CCP, RF and history of diabetes (model B). Both models showed a great area under the curve of ROC for either the training cohort or the validation cohort. The data indicated that the novel RA diagnostic models possessed an advantageous discrimination capacity and application potential. Conclusion Serum SAA4 has utility as a biomarker for RA’s diagnosis and can enhance the detection of RA when combined with anti-CCP.

Bilateral Differential Topography—A Novel Topographic Algorithm for Keratoconus and Ectatic Disease Screening

Purpose: The purpose of this study was to establish a novel bilateral differential topographic algorithm and assess its efficacy for screening of keratoconus and corneal ectasia before corneal refractive surgery.Methods: One hundred and sixty-one consecutive patients (115 men and 46 women, aged 22.8 ± 6.8 years) with keratoconus, including clinical keratoconus, subclinical keratoconus, forme fruste keratoconus (FFK), and corneal ectasia (KC group) and one hundred and seventy-four consecutive patients (97 men and 77 women, aged 25.1 ± 6.7 years) with ametropia (control group) visiting the Eye and ENT hospital of Fudan University from June 2018 to April 2021 were included. Bilateral differential keratometry, elevation, and pachymetry topographies were composed based on raw topographic data obtained by a Scheimpflug imaging anterior segment analyzer. Key bilateral differential characteristic parameters were calculated. SPSS 20 (SPSS Inc., IBM) was used for statistical analyses and the receiver operating characteristic (ROC) curves were used to determine the diagnostic efficacies.Results: Mann-Whitney tests detected that the front keratometry, front elevation, corneal pachymetry, and back elevation maximal, mean, and standard deviation values within a 1.5-mm radius of the bilateral differential topography were all significantly higher in the KC group than in the control group (all p-values &lt;0.001). The front keratometry mean (ΔFKmean) and standard deviation (ΔFKsd) and the front elevation standard deviation (ΔFEsd) and maximal (ΔFEmax) values within a 1.5-mm radius of the bilateral differential topography yielded the four highest accuracies (area under the ROC curve = 0.985, 0.985, 0.984, and 0.983, respectively) for discriminating KC cases (including FFK cases) from normal cases. Cut-off values of 0.75 diopters (D) for the ΔFKmean, 0.67 D for the ΔFKsd, 2.9 μm for the ΔFEsd, and 14.6 μm for the ΔFEmax had the highest sensitivities (95.7, 95.0, 96.9, and 95.0%, respectively) and specificities (96.0, 97.7, 94.8, and 95.4%, respectively).Conclusion: Bilateral differential topographic parameters may be efficient for the early detection of keratoconus and corneal ectasia secondary to corneal refractive surgery. This bilateral differential topographic algorithm may complement conventional diagnostic models by improving the sensitivity and specificity of screening for early keratoconus and ectasia before corneal refractive surgeries.

Research of diagnostic models of subsystems of power supply of radioelectronic means

The complex indicator of the reliability of electronic means - the readiness factor - significantly depends on the average recovery time. At the same time, the largest labor costs are spent by repair specialists on finding a faulty element. Diagnostic repair support depends on the models used in the development of defect detection algorithms. The most common use of diagnostic models in the form of a graph of information and energy connections, which consists of three types of structures: sequential connection of elements, converging and diverging. The latter did not receive the necessary research. In the article as a result of research of influence of forms of the graph of information and power communications on indicators of quality of diagnostic maintenance of subsystems of power supply of radio electronic means analytical dependences of quantitative estimation of the controlled variables on average recovery time are received for the first time. This allows to improve the quality of diagnostic support of existing and promising samples during their design. Minimization of diagnostic errors makes it possible to verify the feasibility of using diagnostic and metrological support during the current repair of electronic devices by the aggregate method, which reduces the recovery time, especially in the field. Depending on the volume of initial data, possible methods for quantifying the probability of the preferred choice of branches of power subsystems of radio electronic means, which also reduces the average recovery time by checking primarily the least reliable and do not require much time to perform checks and troubleshooting. The obtained results should be used in improving the diagnostic and metrological support of power supply subsystems of existing electronic devices and its development for promising samples in order to improve the quality of maintenance, regardless of the structure of choice.

Development and external validation of a nomogram for neurosyphilis diagnosis among non-HIV patients: a cross-sectional study

Background The diagnosis of neurosyphilis is challenging due to the requirement of a lumbar puncture and cerebrospinal fluid (CSF) laboratory tests. Therefore, a convenient diagnostic nomogram for neurosyphilis is warranted. This study aimed to construct diagnostic models for diagnosing neurosyphilis. Methods This cross-sectional study included data of two patient cohorts from Western China Hospital of Sichuan University between September 2015 and April 2021 and Shangjin Hospital between September 2019 and April 2021 as the development cohort and the external validation cohort, respectively. A diagnostic model using logistic regression analysis was constructed to readily provide the probability of diagnosis at point of care and presented as a nomogram. The clinical usefulness of the diagnostic models was assessed using a receiver operating characteristic (ROC) and Harrell concordance (Harrell C) index for discrimination and calibration plots for accuracy, which adopted bootstrap resampling 500 times. Results One hundred forty-eight and 67 patients were included in the development and validation cohorts, respectively. Of those, 131 were diagnosed as having reactive neurosyphilis under the criteria of positive results in both CSF treponemal and non-treponemal tests. In the development cohort, male, psychiatric behaviour disorders, and serum toluidine red unheated serum test were selected as diagnostic indicators applying a stepwise procedure in multivariable logistic model. The model reached 80% specificity, 79% sensitivity, and 0·85 area under the curves (AUC) (95% confidence interval, 0·76–0·91). In the validation cohorts, the Harrell C index for the diagnostic possibility of reactive neurosyphilis was 0·71. Conclusions A convenient model using gender, presence of psychiatric behaviour disorders, and serum TRUST titre was developed and validated to indicate diagnostic results in patients suspected of neurosyphilis. Checking the model value of factors on nomogram is a feasible way to assist clinicians and primary health servers in updating patients’ medical charts and making a quantitatively informed decision on neurosyphilis diagnosis. Trial registration This research was retrospectively registered in the Ethics committee on biomedical research, West China Hospital of Sichuan University. The research registration and committee’s reference number was 1163 in 2020 approval.

Distance learning of foreign languages for students of economic specialties

Distance education at lightning-fast speed has become the only possible form of education. Distance learning of a foreign language for students of higher educational institutions has a number of advantages due to the fact that we are talking about pedagogical interaction with the age group of psychologically mature individuals with relatively formed mechanisms of motivation and outlined personal and professional orientation. The purpose of the present research is a comprehensive analysis of the process and results of distance learning of a foreign language (English) for students of economic specialties. The research methods are as follows: the analysis of modern opportunities for organizing distance learning; study of theoretical and methodological papers on the subject matter; method of experimental teaching of foreign languages with an emphasis on tactics of stimulating the personal and motivational sphere of students’ educational activities; development of author’s diagnostic models in order to reveal the dynamics of development of knowledge and practical skills in a foreign language of students of economic profile; qualitative and quantitative analysis of empirical data; statistical and mathematical interpretation of results, their functional analysis; method of generalization and abstraction. According to the data obtained, the hypothesis of the research has been confirmed.

A DIFFERENTIATED APPROACH TO THE DIAGNOSIS OF OCCLUSIVE DISORDERS AT THE STAGES OF FUNCTIONAL EXAMINATION OF THE CHEWING APPARATUS

Occlusion is a harmonious interaction of the dental system in dynamics, ending with the contact of teeth in conditions of their normal or disturbed ratio. This is a complex action involving teeth, masticatory muscles, TMJ. Occlusive disorders are a reflection of the external manifestations of pathological processes of the dental system. There is no doubt that in the search for etiological factors of occlusion disorders, the problem will manifest itself in one of the parts of the chewing system. The aim of the study was to optimize the early diagnosis of occlusive disorders in young patients without violating the integrity of the dentition. Materials and methods. The study included 36 patients without a violation of the integrity of the dentition aged 18 to 25 years (15 men, 21 women), who did not complain of pain in the dental system. A comprehensive dental examination was carried out and an individual "questionnaire and patient's health card" was filled out. Computer analysis with the T-Scan III occlusiography system of the company Tekscan (USA) was used to register the nature of the closing of the dentition, the study of diagnostic models in the PROTAR evo 7 KAVO articulator, as well as the study of the registration of the difference in the biopotentials of the masticatory and temporal muscles proper in patients in the phase of relative physiological rest and with maximum jaw compression using a four-channel electromyograph Synapsis NMF Neurotech (Russia). The results showed that the prevalence of occlusive disorders in the study group is 83.3%. The abnormal position of the teeth in the dentition in combination with malocclusion anomalies, non-physiological relief of the occlusal surfaces of the teeth formed due to various factors which cause the appearance of premature contacts. This prevents the harmonious sliding movements of the lower jaw and is accompanied by articulatory changes in the entire chewing system.

Experiments with Social Good: Feminist Critiques of Artificial Intelligence in Healthcare in India

In contemporary India, AI-enabled automated diagnostic models are beginning to control who gets access to what kind of medical care, with the most invasive systems being aimed at underserved communities. I critically question the dominant narrative of “AI for social good” that has been widely adopted by various stakeholders in the healthcare industry towards solving development challenges through the introduction of AI applications targeted towards the sick-poor. Using feminist theory, I argue that AI systems should not be seen as neutral products but complex sociotechnical processes embedded with gendered knowledge and labor. I analyze the layers of expropriation and experimentation that come into play when AI technologies become a method of using diverse bodies and medical records of the sick-poor as data to train proprietary AI algorithms at a low cost in the absence of effective state regulatory mechanisms. I posit that an overwhelming focus on “spectacular technologies” such as AI derails public efforts from solving the actual needs of populations targeted by the “AI for social good” narrative, and from the development of sustainable, responsible, situated healthcare solutions. Lastly, I offer social and policy recommendations that would enable us to envision inclusive feminist futures in which we understand and prioritize the needs of underserved populations over capitalist market logics in the development, deployment, and regulation of AI systems.

Detection and verification of coexisting diagnostic markers in plasma and serum of patients with non-small-cell lung cancer

Aim: To screen and identify the potential biomarkers co-existing in plasma and serum of patients with non-small-cell lung cancer (NSCLC), and establish appropriate diagnostic models. Methods: A cohort of 195 plasma samples and 180 serum samples were obtained from healthy controls (HC), adenocarcinoma (AdC) and squamous cell carcinoma (SqCC) patients enrolled from the First Affiliated Hospital of Nanjing Medical University. Metabolites in plasma and serum were analyzed by GC-MS. Results: Hypoxanthine was found to have good performance in the differential diagnosis of NSCLC (including AdC and SqCC) and HC (area under the receiver operating characteristic [AUROC] ≥0.85). Combinations of metabolites could be used for differential diagnosis of NSCLC and HC (AUROC >0.93), AdC and HC (AUROC >0.91), SqCC and HC (AUROC >0.95), AdC and SqCC (AUROC >0.72). Conclusions: Metabolomics based on GC-MS can screen and identify the differential metabolites coexisting in plasma and serum of patients with NSCLC, and prediction models established by this method can be used for the differential diagnosis of patients with NSCLC.