Sensitivity Rate Research Articles

Evaluation and comparison of one-step real-time PCR and one-step RT-LAMP methods for detection of SARS-CoV-2

BackgroundThere is an increasing disease trend for SARS-COV-2, so need a quick and affordable diagnostic method. It should be highly accurate and save costs compared to other methods. The purpose of this research is to achieve these goals.MethodsThis study analyzed 342 samples using TaqMan One-Step RT-qPCR and fast One-Step RT-LAMP (Reverse Transcriptase Loop-Mediated Isothermal Amplification). The One-Step LAMP assay was conducted to assess the sensitivity and specificity.ResultsThe research reported positive samples using two different methods. In the RT-LAMP method, saliva had 92 positive samples (26.9%) and 250 negative samples (73.09%) and nasopharynx had 94 positive samples (27.4%) and 248 negative samples (72.51%). In the RT-qPCR method, saliva had 86 positive samples (25.1%) and 256 negative samples (74.8%) and nasopharynx had 93 positive samples (27.1%) and 249 negative samples (72.8%). The agreement between the two tests in saliva and nasopharynx samples was 93% and 94% respectively, based on Cohen’s kappa coefficient (κ) (P < 0.001). The rate of sensitivity in this technique was reported at a dilution of 1 × 101 and 100% specificity.ConclusionsBased on the results of the study the One-Step LAMP assay has multiple advantages. These include simplicity, cost-effectiveness, high sensitivity, and specificity. The One-Step LAMP assay shows promise as a diagnostic tool. It can help manage disease outbreaks, ensure prompt treatment, and safeguard public health by providing rapid, easy-to-use testing.

From exposure to control: the application of allergen component-resolved diagnosis in the clinical management of cockroach allergies

Cockroaches are one of the most common indoor allergens worldwide, and exposure to cockroach allergens (such as the insect body, debris, and secretions) can trigger severe allergic rhinitis and(or) asthma. Currently, the World Health Organization (WHO)/International Union of Immunological Societies (IUIS) has identified 32 allergenic components in cockroaches, but none of these allergens have shown a clear immunodominance. The sensitization rate to cockroach allergens shows significant variability across different regions and populations and exhibits cross-reactivity with various invertebrates, increasing the complexity of clinical diagnosis and treatment. This article delves into the "Molecular Allergology User's Guide 2.0"(MAUG 2.0) published by the European Academy of Allergy and Clinical Immunology (EAACI) and the research progress on cockroach allergies both domestically and internationally. It elucidates the crucial role of allergen component diagnostic technology in enhancing the diagnosis and treatment of cockroach-induced allergic diseases, efficiently assisting clinicians in identifying common sensitizations and cross-reactivities, thereby offering patients more accurate diagnoses and personalized treatment plans.

Molecular Characterization of Lineage-IV Peste Des Petits Ruminants Virus and the Development of In-House Indirect Enzyme-Linked Immunosorbent Assay (IELISA) for its Rapid Detection”

Peste des petits ruminants (PPRV), a highly contagious viral disease, causes significant economic losses concerning sheep and goats. Recently, PPR viruses (PPRVs), have adopted new hosts and lineage IV of PPRVs represents genetic diversity within the same lineage. 350 samples, including blood, swabs, and tissues from sheep/goats, were collected during the 2020–2021 disease outbreaks in Pakistan. These samples were analysed through RT-PCR and three isolates of PPRV with accession numbers, MW600920, MW600921, and MW600922, were submitted to GenBank, based on the partial N-gene sequencing. This analysis provides a better understanding of genetic characterizations and a targeted RT-PCR approach for rapid PPRV diagnosis. An IELISA test was developed using the semi-purified antigen MW600922 isolate grown in Vero cells. The PPRV isolates currently present high divergence with the Turkish strain; conversely, similarities equivalent to 99.73% were observed for isolates collected from Pakistan. The developed indirect ELISA (IELISA) test demonstrated antibody detection rates at dilutions of 1:200 for antibodies (serum) and 1:32 for antigens. In comparison to cELISA, high specificity (85.23%) and sensitivity (90.60%) rates were observed. In contrast to the virus neutralization test (VNT), IELISA was observed to be 100% specific and 82.14% sensitive in its results. Based on these results, serological surveys conducted for PPR antibodies using IELISA can be a more effective strategy on a larger scale. Furthermore, our results demonstrate a significant breakthrough in the research in terms of cost-effectiveness and storage efficiency, and the developed IELISA test is highly recommended for use in developing countries.

Bayesian Networks for Prescreening in Depression: Algorithm Development and Validation.

Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications. This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and propose tools that can be used in real-world applications. The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (PesquisaNacionalde Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian network was used for feature selection. Selected features were then used to train machine learning models to predict DS, operationalized as a score of ≥10 on the 9-item Patient Health Questionnaire. The study also analyzed the impact of varying sensitivity rates on the reduction of screening interviews compared to a random approach. The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by maximizing the Youden index, the models achieved sensitivities of 0.717, 0.741, and 0.718, and specificities of 0.644, 0.737, and 0.766 for PROACTIVE, PNS 2013, and PNS 2019, respectively. The area under the receiver operating characteristic curve was 0.736, 0.801, and 0.809 for these 3 data sets, respectively. For the PROACTIVE data set, the most influential features identified were postural balance, shortness of breath, and how old people feel they are. In the PNS 2013 data set, the features were the ability to do usual activities, chest pain, sleep problems, and chronic back problems. The PNS 2019 data set shared 3 of the most influential features with the PNS 2013 data set. However, the difference was the replacement of chronic back problems with verbal abuse. It is important to note that the features contained in the PNS data sets differ from those found in the PROACTIVE data set. An empirical analysis demonstrated that using the proposed model led to a potential reduction in screening interviews of up to 52% while maintaining a sensitivity of 0.80. This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach has the potential to substantially reduce the number of screening interviews while maintaining high sensitivity, thereby facilitating improved early identification and intervention strategies for individuals experiencing DS.

P-554 Artificial intelligence (AI) for embryo genetic risk assessment: a novel form of preimplantation genetic screening

Abstract Study question Can an AI-based embryo ploidy screening tool effectively provide a genetic risk assessment on Day 5 embryos? Summary answer AI screening results showed strong predictive value for early detection of at-risk embryos warranting confirmatory diagnostic testing, based only on time lapse video assessment. What is known already Euploid embryo transfer is the dogma of IVF success. Embryo evaluation relies extensively on diagnostic preimplantation genetic testing for aneuploidy (PGT-A) by means of trophectoderm biopsy. Though pivotal, this presents substantial practical and financial limitations. There is demand for an alternative genetic screening method that provides a quantitative embryo genetic risk assessment for patients who opt out of invasive diagnostic testing, or who intend to undergo fresh transfer. These results can provide information for understanding your aneuploidy risk for more precise prognosis counseling and testing. This is important since diagnostic tests may incur excess financial burden, inconclusive outcomes, and time-to-results. Study design, size, duration Time lapse videos (N = 5,000) were used for AI training. The AI core architecture was a video transformer model for spatio-temporal video sampling. Known ploidy and live-birth results were used as ground truth, with maternal age and embryo quality scores incorporated as input parameters during calibrated logistic regression. A blind test dataset (N = 708 embryos; euploid=352; aneuploid=356; mean ± SD patient age: 35.9 ± 5.4 years) was used to evaluate predictive accuracy. Participants/materials, setting, methods The AI outputs a scalar (1-99) that associates with euploidy likelihood. The AI’s screening value was determined by its specificity (correct prediction of aneuploid), sensitivity (correct prediction of euploid), false positive, and false negative rate. We determined optimal AI score thresholds that identified high aneuploidy and euploidy risk categories (AI score &amp;lt;33; AI score &amp;gt;66, respectively). Main results and the role of chance Specificity of the AI screening test was 83.0%, with a sensitivity of 56.0%. The false positive rate was 26.7% and the false negative rate was 29.3%. The AI’s high specificity relative to its sensitivity shows its clinical value to deselect embryos with the strongest risk of genetic abnormality, and for the prioritization of embryos for confirmatory PGT. Boxplot visualization of the full AI score distribution showed successful discrimination between aneuploid and euploid embryos (mean AI score for aneuploid and euploid were 51.3 and 43.5, respectively) with appropriately minimized overlapping of the interquartile range. The optimal AI score thresholds for detecting embryos with the highest and lowest likelihoods of euploidy were &amp;gt;66 /&amp;lt;33, respectively, representing 71% likelihood of euploidy for the &amp;gt;66 group and 72% aneuploidy for the &amp;lt;33 group. Limitations, reasons for caution The screening does not provide diagnostic genetic testing on the chromosome level. The influence of mosaicism on the false positive/negative rates was not assessed. Wider implications of the findings Results support the use of an AI ploidy screening test for effective decision-making and triage of at-risk embryos for transfer or confirmatory diagnostic testing via PGT-A. Trial registration number Not applicable

Food safety control in poultry industry: prevalence and antimicrobial susceptibility of Escherichia coli isolated from raw chicken and the potential use of Origanum essential oils as alternative to antibiotics

ABSTRACT 1. The extensive use of antimicrobials in poultry production may contribute to the emergence of resistant bacteria. This study was conducted to determine the prevalence and resistance of different E. coli strains isolated from raw chicken meat and to investigate the possibility to use Lebanese native oregano essential oils as alternatives. 2. In total, 250 chickens from Lebanese markets were examined for the presence of E. coli. Isolates were then screened for susceptibility using 19 antibiotics and two essential oils extracted from oregano plants. 3. Of the 250 chickens tested, 80% were contaminated with E. coli. Main resistance was seen against amoxycillin, ampicillin, penicillin, tetracycline, tylosin, streptomycin and erythromycin. The highest rate of sensitivity was found in 86.1% of strains to Amoxycillin/Clavulanic acid, 80.09% to Tilmicosin. Both essential oils from Origanum syriacum (98%) and O. ehrenbergii (97.3%) showed promising potential in inhibiting the growth of the tested bacteria. Oil from O. syriacum exhibited superior efficacy against 200 E. coli strains, inhibiting 46.1% at 200 mg/l and all at 400 mg/l, while O. ehrenbergii oil showed slightly lower inhibition, affecting 41.6% at 200 mg/l and all at 400 mg/l.

Biofilm-producing ability of methicillin-resistant Staphylococcus aureus clinically isolated in China

BackgroundStaphylococcus aureus, a commensal bacterium, colonizes the skin and mucous membranes of approximately 30% of the human population. Apart from conventional resistance mechanisms, one of the pathogenic features of S. aureus is its ability to survive in a biofilm state on both biotic and abiotic surfaces. Due to this characteristic, S. aureus is a major cause of human infections, with Methicillin-Resistant Staphylococcus aureus (MRSA) being a significant contributor to both community-acquired and hospital-acquired infections.ResultsAnalyzing non-repetitive clinical isolates of MRSA collected from seven provinces and cities in China between 2014 and 2020, it was observed that 53.2% of the MRSA isolates exhibited varying degrees of ability to produce biofilm. The biofilm positivity rate was notably high in MRSA isolates from Guangdong, Jiangxi, and Hubei. The predominant MRSA strains collected in this study were of sequence types ST59, ST5, and ST239, with the biofilm-producing capability mainly distributed among moderate and weak biofilm producers within these ST types. Notably, certain sequence types, such as ST88, exhibited a high prevalence of strong biofilm-producing strains. The study found that SCCmec IV was the predominant type among biofilm-positive MRSA, followed by SCCmec II. Comparing strains with weak and strong biofilm production capabilities, the positive rates of the sdrD and sdrE were higher in strong biofilm producers. The genetic determinants ebp, icaA, icaB, icaC, icaD, icaR, and sdrE were associated with strong biofilm production in MRSA. Additionally, biofilm-negative MRSA isolates showed higher sensitivity rates to cefalotin (94.8%), daptomycin (94.5%), mupirocin (86.5%), teicoplanin (94.5%), fusidic acid (81.0%), and dalbavancin (94.5%) compared to biofilm-positive MRSA isolates. The biofilm positivity rate was consistently above 50% in all collected specimen types.ConclusionsMRSA strains with biofilm production capability warrant increased vigilance.

Computational Modeling Differentiates Learning Rate From Reward Sensitivity Deficits Produced by Early-Life Adversity in a Rodent Touchscreen Probabilistic Reward Task

BackgroundExposure to adversity, including unpredictable environments, during early life is associated with neuropsychiatric illness in adulthood. One common factor in this sequela is anhedonia, the loss of responsivity to previously reinforcing stimuli. To accelerate the development of new treatment strategies for anhedonic disorders induced by early-life adversity, animal models have been developed to capture critical features of early-life stress and the behavioral deficits that such stressors induce. We have previously shown that rats exposed to the limited bedding and nesting protocol exhibited blunted reward responsivity in the probabilistic reward task, a touchscreen-based task reverse translated from human studies. MethodsTo test the quantitative limits of this translational platform, we examined the ability of Bayesian computational modeling and probability analyses identical to those optimized in previous human studies to quantify the putative mechanisms that underlie these deficits with precision. Specifically, 2 parameters that have been shown to independently contribute to probabilistic reward task outcomes in patient populations, reward sensitivity and learning rate, were extracted, as were trial-by-trial probability analyses of choices as a function of the preceding trial. ResultsSignificant deficits in reward sensitivity, but not learning rate, contributed to the anhedonic phenotypes in rats exposed to early-life adversity. ConclusionsThe current findings confirm and extend the translational value of these rodent models by verifying the effectiveness of computational modeling in distinguishing independent features of reward sensitivity and learning rate that complement the probabilistic reward task’s signal detection end points. Together, these metrics serve to objectively quantify reinforcement learning deficits associated with anhedonic phenotypes.

Development of a natural language processing algorithm for the detection of spinal metastasis based on magnetic resonance imaging reports

BackgroundMetastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system to identify and refer patients with spinal metastases can help overcome barriers to timely treatment. We describe the training, optimization and validation of a natural language processing algorithm to identify the presence of vertebral metastasis and metastatic epidural cord compression (MECC) from radiology reports of spinal MRIs. MethodsReports from patients with spine MRI studies performed between January 1, 2008 and April 14, 2019 were reviewed by a team of radiologists to assess for the presence of cancer and generate a labeled dataset for model training. Using regular expression, impression sections were extracted from the reports and converted to all lower-case letters with all nonalphabetic characters removed. The reports were then tokenized and vectorized using the doc2vec algorithm. These were then used to train a neural network to predict the likelihood of spinal tumor or MECC. For each report, the model provided a number from 0 to 1 corresponding to its impression. We then obtained 111 MRI reports from outside the test set, 92 manually labeled negative and 19 with MECC to test the model's performance. ResultsAbout 37,579 radiology reports were reviewed. About 36,676 were labeled negative, and 903 with MECC. We chose a cutoff of 0.02 as a positive result to optimize for a low false negative rate. At this threshold we found a 100% sensitivity rate with a low false positive rate of 2.2%. ConclusionsThe NLP model described predicts the presence of spinal tumor and MECC in spine MRI reports with high accuracy. We plan to implement the algorithm into our EMR to allow for faster referral of these patients to appropriate specialists, allowing for reduced morbidity and increased survival.

Assessment of clinical phenotypic characteristics of patients with angioedema without wheals in a turkish population.

Background: Angioedema (AE) is defined as localized, self-limited swelling of subcutaneous tissues and mucosa. Objective: The aim of this study was to compare the phenotypic characteristics of patients with AE without wheals. Methods: This prospective study included adult patients with recurrent AE without wheals. Demographic and laboratory data of the patients were recorded in the patient file when they presented to the outpatient clinic between August 2018 and August 2020. The patients were contacted by phone to evaluate whether their AE had gone into remission between October 2023 and January 2024. The phenotypic characteristics of AE subtypes were compared. Results: The study included a total of 143 patients. The average age, age of onset of AE, rates of diabetes mellitus, hypertension and coronary artery disease were higher in the patients with angiotensin-converting enzyme inhibitor (ACEI) use related acquired AE (AAE) (AAE-ACEI). The rates of allergic rhinitis, drug allergy, atopy, and aeroallergen sensitivity, and the median total immunoglobulin E level were higher in patients with idiopathic histaminergic AAE (AAE-IH). The rate of face and/or perioral AE attacks was higher in the patients with AAE-ACEI, AAE-IH, and idiopathic non-histaminergic AAE. The rate of AE attacks in limbs, abdominal, genital and other parts of the body was higher in patients with hereditary AE (HAE). The baseline AE activity score was lower in the patients with AAE-IH and higher in the patients with HAE. In long-term follow-up, the remission rate of AE attacks was significant higher in patients with AAE-ACEI and AAE-IH. Conclusion: The phenotypic characteristic features of Turkish patients with AE without wheals may vary, depending on the underlying AE pathogenesis. C1 inhibitor level and function, complement C4 and C1q, and genetic tests contributed to the diagnosis; other laboratory tests did not contribute to the diagnosis.

Predicting severe outcomes in pediatric trauma patients: Shock index pediatric age-adjusted vs. age-adjusted tachycardia

IntroductionWhen an injured patient arrives in the Emergency Department (ED), timely and appropriate care is crucial. Shock Index Pediatric Age-Adjusted (SIPA) has been shown to accurately identify pediatric patients in need of emergency interventions. However, no study has evaluated SIPA against age-adjusted tachycardia (AT). This study aims to compare SIPA with AT in predicting outcomes such as mortality, severe injury, and the need for emergent intervention in pediatric trauma patients. Material and methodsThis is a retrospective cross-sectional analysis of patient data abstracted from the Trauma Quality Improvement Program Participant Use Files (TQIP PUFs) for years 2013–2020. Patients aged 4–16 with blunt mechanism of injury and injury severity score (ISS) > 15 were included. 36,517 children met this criteria. Sensitivity, specificity, overtriage, and undertriage rates were calculated to compare the effectiveness of AT and elevated SIPA as predictors of severe injuries and need for emergent intervention. Emergent interventions included craniotomy, endotracheal intubation, thoracotomy, laparotomy, or chest tube placement within 24 h of arrival. ResultsAT classified 59% of patients as “high risk,” while elevated SIPA identified 26%. Compared to AT patients, a greater proportion of patients with elevated SIPA required a blood transfusion within 24 h (22% vs. 12%, respectively; p < 0.001). In-hospital mortality was higher for the elevated SIPA group than AT (10% vs. 5%, respectively; p < 0.001) as well as the need for emergent operative interventions (43% vs. 32% respectively; p < 0.001). Grade 3 or higher liver/spleen lacerations requiring blood transfusion were also more common among elevated SIPA patients than AT patients (8% vs. 4%, respectively; p < 0.001). AT demonstrated greater sensitivity but lower specificity compared to SIPA across all outcomes. AT showed improved overtriage and undertriage rates compared to SIPA, but this is attributed to identifying a large proportion of the sample as “high risk.” ConclusionsAT outperforms SIPA in sensitivity for mortality, injury severity and emergent interventions in pediatric trauma patients while the specificity of SIPA is high across these outcomes.

Extended nnU-Net for Brain Metastasis Detection and Segmentation in Contrast-Enhanced Magnetic Resonance Imaging With a Large Multi-Institutional Data Set

PurposeTo investigate an extended self-adapting nnU-Net framework for detecting and segmenting brain metastases (BM) on MRI. ApproachSix different nnU-Net systems with adaptive data sampling, adaptive Dice loss (ADL) or different patch/batch sizes were trained and tested for detecting and segmenting intraparenchymal BM with a size ≥ 2 mm on 3D post-Gd T1-weighted MRI volumes using 2092 patients from seven institutions (1712, 195 and 185 patients for training, validation and testing, respectively). Gross tumor volumes (GTVs) of BM delineated by physicians for stereotactic radiosurgery (SRS) were collected retrospectively and curated at each institute. Additional centralized data curation was carried out to create GTVs of uncontoured BM by two radiologists to improve accuracy of ground truth. The training dataset was augmented with synthetic BMs of 1025 MRI volumes using a 3D generative pipeline. BM detection was evaluated by lesion-level sensitivity and false-positive (FP) rate. BM segmentation was assessed by lesion-level Dice similarity coefficient (DSC), 95-percentile Hausdorff distance (HD95) and average HD. The performances were assessed across different BM sizes. Additional testing was performed using a second dataset of 206 patients. ResultsOf the six nnU-Net systems, the nnU-Net with ADL achieved the best detection and segmentation performance on the first testing dataset. At an FP rate of 0.65±1.17, overall sensitivity was 0.904 for all sizes of BM, 0.966 for BM ≥ 0.1 cm3 and 0.824 for BM < 0.1 cm3. Mean values of DSC, HD95 and average HD of all detected BMs were 0.758, 1.45 mm and 0.23 mm, respectively. Performances on the second testing dataset achieved sensitivity of 0.907 at an FP rate of 0.57±0.85 for all BM sizes, and average HD of 0.33 mm for all detected BM. ConclusionsOur proposed extension of the self-configuring nnU-Net framework substantially improved small BM detection sensitivity while maintaining a controlled FP rate. Clinical utility of the extended nnU-Net model for assisting early BM detection and SRS planning will be investigated.

Daily Social Isolation Maps Onto Distinctive Features of Anhedonic Behavior: A Combined Ecological and Computational Investigation

BackgroundLoneliness and social isolation have detrimental consequences for mental health and act as vulnerability factors for the development of depressive symptoms, such as anhedonia. The mitigation strategies used to contain COVID-19, such as social distancing and lockdowns, allowed us to investigate putative associations between daily objective and perceived social isolation and anhedonic-like behavior. MethodsReward-related functioning was objectively assessed using the Probabilistic Reward Task. A total of 114 unselected healthy individuals (71% female) underwent both a laboratory and an ecological momentary assessment. Computational modeling was applied to performance on the Probabilistic Reward Task to disentangle reward sensitivity and learning rate. ResultsFindings revealed that objective, but not subjective, daily social interactions were associated with motivational behavior. Specifically, higher social isolation (less time spent with others) was associated with higher responsivity to rewarding stimuli and a reduced influence of a given reward on successive behavioral choices. ConclusionsOverall, the current results broaden our knowledge of the potential pathways that link (COVID-19–related) social isolation to altered motivational functioning.

Screening Outcomes of Mammography with AI in Dense Breasts: A Comparative Study with Supplemental Screening US.

Background Comparative performance between artificial intelligence (AI) and breast US for women with dense breasts undergoing screening mammography remains unclear. Purpose To compare the performance of mammography alone, mammography with AI, and mammography plus supplemental US for screening women with dense breasts, and to investigate the characteristics of the detected cancers. Materials and Methods A retrospective database search identified consecutive asymptomatic women (≥40 years of age) with dense breasts who underwent mammography plus supplemental whole-breast handheld US from January 2017 to December 2018 at a primary health care center. Sequential reading for mammography alone and mammography with the aid of an AI system was conducted by five breast radiologists, and their recall decisions were recorded. Results of the combined mammography and US examinations were collected from the database. A dedicated breast radiologist reviewed marks for mammography alone or with AI to confirm lesion identification. The reference standard was histologic examination and 1-year follow-up data. The cancer detection rate (CDR) per 1000 screening examinations, sensitivity, specificity, and abnormal interpretation rate (AIR) of mammography alone, mammography with AI, and mammography plus US were compared. Results Among 5707 asymptomatic women (mean age, 52.4 years ± 7.9 [SD]), 33 (0.6%) had cancer (median lesion size, 0.7 cm). Mammography with AI had a higher specificity (95.3% [95% CI: 94.7, 95.8], P = .003) and lower AIR (5.0% [95% CI: 4.5, 5.6], P = .004) than mammography alone (94.3% [95% CI: 93.6, 94.8] and 6.0% [95% CI: 5.4, 6.7], respectively). Mammography plus US had a higher CDR (5.6 vs 3.5 per 1000 examinations, P = .002) and sensitivity (97.0% vs 60.6%, P = .002) but lower specificity (77.6% vs 95.3%, P < .001) and higher AIR (22.9% vs 5.0%, P < .001) than mammography with AI. Supplemental US alone helped detect 12 cancers, mostly stage 0 and I (92%, 11 of 12). Conclusion Although AI improved the specificity of mammography interpretation, mammography plus supplemental US helped detect more node-negative early breast cancers that were undetected using mammography with AI. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Whitman and Destounis in this issue.

Deltoid tuberosity index for proximal humerus fracture: reliability and a predictor of systemic osteoporosis in an Asian population

Our study investigates the reliability of deltoid tuberosity index (DTI) and DTI as a predictor of systemic osteoporosis. The proximal humerus is a common fragility fracture. Current literature suggests that poor local bone density is a significant predictor for surgical fixation failure. The DTI is a simple radiographical tool that is strongly correlates with local humeral BMD aiding surgical planning to consider adjuncts or arthroplasty. However, there is a lack of data in the reliability of assessment of DTI, as well as its correlation to systemic osteoporosis. Respective cohort of patients with PHF treated at a trauma center in Singapore from August 2017 to July 2018 were recruited. Four raters at different levels of varying clinical seniority measured DTI using shoulder radiographs. The dual energy X-ray Absorptiometry (DEXA) bone mineral density (BMD) scan of the hip and lumbar spine was used to diagnose osteoporosis. Area under receiver operating characteristics (AUROC) analysis was conducted to study the diagnostic utility of DTI to predict the risk of osteoporosis. Our study had 87 patients consisting 18 males and 69 females, mainly of Chinese ethnicity (84%) and mean age of 69.7 years (SD 9.52, range 39-92yrs). For assessment of DTI, there was good intra-rater reliability amongst four raters (correlation coefficient range 0.805- 0.843) and excellent inter-rater reliability between al raters (intraclass correlation coefficient = 0.898; 95% CI 0.784-0.950, p-value <0.001). Based on BMD, 55.2% (n=48) were osteoporotic using T-score <-2.5. The highest correlation of DTI to BMD was with femoral neck density at 0.580. The DTI cut-off of 1.6 had the highest combined sensitivity and false positive rate, with area under curve (AUC) = 0.682 (95% CI, 0.564-0.799) for the overall population and AUC =0.706 (95% CI, 0.569-0.842) for patients <75 years. The DTI is a simple and reliable tool, strengthening its applicability in clinical practice to enhance preoperative planning in the surgical fixation of PHF. DTI with a cut off of 1.6 may be helpful tool prompting clinicians to workup and manage underlying osteoporosis.

Antimicrobial Sensitivity of Pseudomonas aeruginosa to Aztreonam, Amoxicillin, Erythromycin, Carbenicillin, Norfloxacin, Chloramphenicol, Gentamycin and Azithromycin after Exposure to Radiation Emitted from Radioactive Sources, Lasers and Exposure to Magn

Objective: The aim of this study to assess the sensitivity of P. aeruginosa for ATM, AML, E, CAR, NOR, CL, CN and AZM after exposure to radiation emitted from radioactive sources, Lasers and exposure to magnetized water. Study design: Cross-sectional in descriptive study design with case–control in analytical study design Backgrounds: P. aeruginosa gram negative bacteria occasion distinct kinds of contagion including epidermis, optics, ears, respiratory tract, urinary tract, intestines derived sepsis, soft tissues, skeleton and joint contagion. Radiation including ionizing and non-ionization depending on the energy of the radiated particles emitted Alpha, Beta and Gamma rays from different radioactive sources. Methodology: Study populations and bacterial deposition and identification of P. aeruginosa. Exposure P. aeruginosa to radiation at different times and doses. Antimicrobial susceptibility test for ATM, AML, E, CAR, NOR, CL, CN and AZM after exposure to radiation emitted from radioactive sources, Lasers and magnetized water. Results: After exposing P. aeruginosa to the Na23, CO60, Cs137 and Sr90 radioactive source without or without aluminum for (1,2,3) hr., the bacteria were examined for antibiotics and the results are high sensitivity to NOR, ATM, CAR. As well as, exposure to Nd: YAG laser in (10, 20) min. with exposure to magnetized water which show high sensitive to NOR and ATM antibiotics. Conclusions: The radioactive sources, Nd: YAG laser and magnetic water have a strong effect on bacteria and their sensitivity to antibiotics, so that their sensitivity rate increased very significantly compared to before exposure. The most effective antibiotics in killing bacteria after exposure are Aztreonam, Norfloxacin, Carbenicillin and Gentamycin (ATM, NOR, CAR and CN).

Hyperspectral image construction in different spectral bands of tea leafs for identifying the tea type using O-ConvNet-RF model

Tea, a commonly consumed beverage, is susceptible to being sold in adulterated or expired forms by third-party vendors. Hyperspectral imaging across different wavelength bands has proven to precisely assess the diverse types of tea and their corresponding financial gains. This study aims to employ a deep learning methodology in conjunction with hyperspectral imaging for efficiently classifying tea leaves. A novel approach is proposed, wherein a waveband convolutional neural network is utilized to generate hyper spectral images of tea leaf samples with enhanced resolution. The model known as optimized-convolutional neural network-random forest O- (ConvNet-RF) demonstrated exceptional performance, achieving high accuracy, impressive recall, F1 score, and notable sensitivity rate, outperforming existing alternative methods. The tea leaf types, namely green, yellow, and black, were accurately identified using a combination of the random forest (RF) model and the O-ConvNet-RF model. The tree-based classification method for the identification of tea leaves demonstrated superior performance as compared to alternative machine learning models. In general, this study presents a successful methodology for the classification of tea leaves, with potential implications for consumer processing and distributor profit analysis.

Diagnostic accuracy of double density sign on CT scan of para-nasal sinuses for fungal sinusitis taking microbiology culture as gold standard.

To compare double-density sign on non-contrast computed tomography scan of paranasal sinuses with fungal sinusitis on histopathology. This prospective study was conducted at the Shifa International Hospital, Islamabad, Pakistan, from July 1, 2021, to June 30, 2023, and comprised patients of either gender aged 20-60 years who were set to undergo functional endoscopic sinus surgery. Demographic characteristics and non-contrast computed tomography scan findings were recorded preoperatively, while microbiological and histopathology results were recorded post-operatively. The microbiological finding was taken as the gold standard. Data was analysed using SPSS 23. Of the 201 patients, 123(61.2%) were males and 78(38.8%) were females. The overall mean age was 41.62±8.52 years. The diagnostic accuracy of a double-density sign on computed tomography scan showed sensitivity 90%, specificity 90.8%, positive predictive value 84%, and negative predictive value 94.4%. A higher rate of sensitivity and specificity indicated that non-contrast computed tomography scan was an effective modality that could be used for the diagnosis of fungal sinusitis.

Pathlength-selective, interferometric diffuse correlation spectroscopy (PaLS-iDCS).

Diffuse correlation spectroscopy (DCS) is an optical method that offers non-invasive assessment of blood flow in tissue through the analysis of intensity fluctuations in diffusely backscattered coherent light. The non-invasive nature of the technique has enabled several clinical applications for deep tissue blood flow measurements, including cerebral blood flow monitoring as well as tumor blood flow mapping. While a promising technique, in measurement configurations targeting deep tissue hemodynamics, the standard DCS implementations suffer from insufficient signal-to-noise ratio (SNR), depth sensitivity, and sampling rate, limiting their utility. In this work, we present an enhanced DCS method called pathlength-selective, interferometric DCS (PaLS-iDCS), which improves upon both the sensitivity of the measurement to deep tissue hemodynamics and the SNR of the measurement using pathlength-specific coherent gain. Through interferometric detection, PaLS-iDCS can provide time-of-flight (ToF) specific blood flow information without the use of expensive time-tagging electronics and low-jitter detectors. The new technique is compared to time-domain DCS (TD-DCS), another enhanced DCS method able to resolve photon ToF in tissue, through Monte Carlo simulation, phantom experiments, and human subject measurements. PaLS-iDCS consistently demonstrates improvements in SNR (>2x) for similar measurement conditions (same photon ToF), and the SNR improvements allow for measurements at extended photon ToFs, which have increased sensitivity to deep tissue hemodynamics (~50% increase). Further, like TD-DCS, PaLS-iDCS allows direct estimation of tissue optical properties from the sampled ToF distribution without the need for a separate spectroscopic measurement. This method offers a relatively straightforward way to allow DCS systems to make robust measurements of blood flow with greatly enhanced sensitivity to deep tissue hemodynamics, enabling further applications of this non-invasive technology.

The effect of genetic alterations detected by the circulating tumor DNA-based next-generation sequencing technique on prognosis and survival in metastatic colorectal cancer

Purpose: Studies conducted to date showed that circulating tumor DNA (ctDNA)-based next generation sequencing (NGS) panels are beneficial in the treatment strategies of patients with metastatic colorectal cancer (mCRC). In this study; we planned to determine the frequencies of various genetic alterations in patients with mCRC by ctDNA-based NGS analyses, evaluate the concordance rates by comparing these results with the results in standard polymerase chain reaction (PCR) analyses, and investigate the effect of the detected alterations on overall survival and progression-free survival. Materials and methods: The study was conducted by retrospective screening and analysis of the data on 48 patients, who were followed up with a diagnosis of mCRC and who received chemotherapy and/or biological agents. The data were analyzed using SPSS 25.0 [IBM SPSS Statistics 25 software (Armonk, NY: IBM Corp.)] package program. Results: In this study, ctDNA-based NGS analyses, compared to the quantitative PCR-based gold standard method, were found to have a sensitivity rate of 64.7%, specificity rate of 55.6% and concordance rate of 59.1% for KRAS mutation; a sensitivity rate of 100%, specificity rate of 86.7% and concordance rate of 87.1% for NRAS mutation; a sensitivity rate of 50%, specificity rate of 96.4% and concordance rate of 90.6% for BRAF mutation. In addition, concordance rates were evaluated based on to the time elapsed between the time of taking the liquid biopsy and tissue biopsy samples. As a result, concordance rates for KRAS, NRAS, and BRAF mutations were found to be 60.9%, 100%, and 100% respectively, in cases where this elapsed time was less than 6 months; and were found to be 57.1%, 78.9%, and 85% respectively, in cases where this elapsed time was more than 6 months. Furthermore, the comprehensive analyzes revealed that the frequency of many molecular changes in mCRC as well as the relationship of these changes with clinicopathological features and survival times. Conclusion: Our study demonstrates the clinical benefit of ctDNA-based NGS analyzes in patients with mCRC.