Average CT Value Research Articles

Relationship between stone volume, average CT value and operation time and efficiency before ureteral soft lens laser lithotripsy.

Soft ureteroscopic holmium laser lithotripsy is becoming increasingly popular as the preferred method for treating mid-to-lower ureteral stones. Studies have indicated that the size, composition, hardness, and fragility of the stones can impact the treatment's effectiveness. To explore the relationship between stone volume, average CT value and operation time and efficiency before ureteral soft lens laser lithotripsy. Our study on 126 patients undergoing ureteroscopic holmium laser lithotripsy for ureteral calculi from May 2020 to January 2022 categorized them into groups based on stone volume and CT value. We compared surgical outcomes and analyzed correlations between stone characteristics, operation parameters, and stone clearance rate to identify independent risk factors influencing treatment efficacy. Group A demonstrated significantly shorter operation durations and lower blood loss compared to Group B, along with higher single stone clearance rates and fewer postoperative complications. Similarly, Group C exhibited shorter operation times, reduced blood loss, higher stone clearance rates, and lower complication rates than Group D. Preoperative stone volume and CT value correlated positively with operation time and stone clearance rate, with both factors identified as independent risk factors affecting ureteral stone clearance following holmium laser lithotripsy. The stone volume and average CT value before ureteral soft lens laser lithotripsy show a positive correlation with operation time and efficiency, indicating that larger stone volumes and higher CT values lead to slower lithotripsy speeds and reduced operation efficiency. Furthermore, preoperative stone volume and average CT value are identified as independent risk factors for residual stones.

Presence of Soya in Industrial and Homemade Sausage Production in Kosovo and Its Reflection on Fatty Acid Profile

In the present study, we investigated to what extent soybean was used in industrial and homemade sausage produced in Kosovo, as well as its potential impact on the fatty acid profile. In total, 63 samples, 42 industrial and 21 traditional sausages, were collected either from the market or the production site. All samples were tested by means of real-time PCR for the detection and quantification of soy content, as well as the GC-FID to determine the potential reflection in the fatty acid profile. The presence of soy DNA was detected in 54 out of 63 samples. In total, 41 out of 42 industrial sausage samples were positive for soy DNA, with an average ct value of 22.60 and a standard deviation (SD) of 4.28, whereas 13 out of 21 traditional sausage samples were positive for soy DNA, with a mean ct value of 23.36 and a standard deviation (SD) of 4.56. There was a statistically significant difference in means between industrial sausage and traditional sausage, with p ≤ 0.001 based on CT values (ANOVA test). We investigated the correlation between ct values in real-time PCR for soy DNA with each fatty acid content. There is a moderate correlation of soy DNA ct values with C16:0 palmitin (decrease), C18:0 stearic acid (decrease), C18:1 oleic acid (increase), and overall saturated fatty acids (decrease). With the exception of C14:0 Myristin, C18:1 oleic, and C20:0 Arachin acids and monosaturated fats, the ANOVA test reveals a significant difference in means between groups for the majority of the fatty acids between industrial sausages and traditional sausages. The current study demonstrates that the fatty acid composition of sausages is influenced by the amount of soy present in them. The extent to which other components affect the fatty acid profile is unknown. However, an increase in oleic acid and a decrease in stearic and overall saturated fatty acids are expected.

A-296 Streck Urine Preserve Provides Sample Stability for Cepheid Xpert CT/NG test

Abstract Background Sexually transmitted infections (STIs) are one of the most common communicable diseases worldwide and are associated with significant morbidity and mortality. Data indicates that the four curable STIs - chlamydia, gonorrhea, trichomoniasis, and syphilis - cause over 375 million infections annually. Further, the infection rate for gonorrhea has increased by 63% in the United States and the emergence of resistant gonorrhea is an urgent global public health concern. To prevent transmission of gonorrhea and other curable STIs and minimize the escalation of untreated infections, early and effective prevention and control strategies are paramount. Rapid diagnostic testing and nucleic acid amplification tests (NAATs) have become the gold standard for STI detection. However, limited global access to these technologies often requires that samples be shipped to central laboratories for analysis. Current protocols recommend that neat urine be analyzed within 24 hours of collection if stored at 2 °C to 8 °C or within four days if frozen, as prolonged storage and exposure to freeze-thaws can induce cell lysis and release of nucleases, leading to degradation of DNA and false negative test results. Without sample stabilization, laboratories are left with a small window for accurate analysis. Here, we demonstrate that Streck Urine Preserve (SUP) maintains target and donor DNA concentrations during prolonged storage and that these stabilized samples are compatible with Cepheid’s automated GeneXpert System and associated Xpert CT/NG test. Methods Fresh human urine, with or without SUP, was tested neat or spiked with Neisseria gonorrhoeae (N. gonorrhoeae). Samples were stored at room temperature for up to 18 days before being analyzed on the Cepheid GeneXpert System using the Xpert CT/NG test per manufacturer’s instructions. Differences in average Ct values were compared for the sample processing control, sample adequacy control, and N. gonorrhoeae targets. DNA stability was assessed by comparing the changes between fresh and SUP-treated samples throughout the study period. Results Following prolonged storage, Ct values for neat, untreated urine increased by 3-7 cycles, correlating to a 10- to 100-fold decrease in detectable copies of N. gonorrhoeae and the sample adequacy control compared to urine samples stabilized with SUP. The average Ct value for samples stabilized with SUP did not change by more than 1.5 cycles throughout the study period. Additionally, Ct values for the sample processing control remained constant throughout the testing period, indicating that SUP did not impact sample processing. Conclusions When limited point-of-care testing options require storage and shipping of samples to central laboratories, urine stabilizers are imperative to obtain results representative of the patient sample at the time of collection. SUP effectively stabilized N. gonorrhoeae DNA and donor DNA prior to analysis with the Cepheid Xpert CT/NG test. This contrasts with the marked decrease in DNA copy number in non-stabilized urine over the study duration, which may lead to false negative results for low-positive urine samples. Taken together, SUP provides clinical researchers and assay developers with added flexibility when handling, shipping, and processing urine specimens and supports compatibility with automated NAAT systems and tests.

Assessment of housekeeping genes stability for gene transcription regulation analysis of Spodoptera littoralis (Lepidoptera: Noctuidae) under Spodoptera littoralis nucleopolyhedrovirus viral infection.

Normalization with respect to stable housekeeping genes is important to facilitate gene transcription regulation research and acquire more accurate quantitative polymerase chain reaction (qPCR) data. In the current study, five candidates housekeeping genes of the cotton leafworm, Spodoptera littoralis encoding for Actin (Actin), elongation factor 1-alpha (EF1α), ribosomal protein S3 (RPS3), ribosomal protein 49 (RP49), and Ubiquitin (Ubi), were evaluated as normalization housekeeping genes under Spodoptera littoralis nucleopolyhedrovirus (SpliNPV) viral infection. The qPCR results confirmed the expression of all five housekeeping genes in S. littoralis viral infected larvae. The expression profiles of the housekeeping genes showed that the EF1α, Actin, and RP49 had the minimum average Ct values of 18.41 ± 0.66, 18.84 ± 0.90 and 19.01 ± 0.87 in all infected samples, respectively. While RPS3 and Ubi showed the maximum average Ct of 21.61 ± 0.51 and 21.11 ± 0.82, respectively. According to the results of ΔCt and geNorm analysis, EF1α was ranked as the most stable housekeeping gene during infection time-course. While by using BestKeeper, geNorm and NormFinder, the Ubi, RP49, and RPS3 showed the most genes transcription stability. The obtained results were also validated using the Cytochrome c oxidase (COX) gene transcripts in response to SpliNPV infection. The results revealed that EF1α and Ubi were the most stable housekeeping genes to be used for normalizing S. littoralis gene transcription regulation under SpliNPV infection. These findings, provide a significant addition for gene transcription regulation studies of S. littoralis upon infection using SpliNPV as a bio-agent.

A retrospective study of 96 cases of adrenal metastases

Objective: To analyze the clinical characteristics, etiological composition, imaging features, and prognosis of adrenal metastases. Methods: This study is a retrospective case series that included 96 patients with pathologically confirmed adrenal metastases who were treated at West China Hospital, Sichuan University, from 2007 to 2017. Clinical features such as sex, age, tumor size, biochemical tests, imaging characteristics, postoperative pathology, treatment methods, and prognosis were collected and analyzed. The prognosis of patients and its influencing factors were analyzed by Kaplan-Meier survival curve and single-factor Cox risk proportional model. Results: Among the 96 included patients, 64 were male and 32 were female, with a median age of 60 years. There were 89 cases of unilateral adrenal metastases, five cases of bilateral metastases, and two cases with unspecified laterality. The median diameter of the metastases was 3.5 cm×2.9 cm, with an average CT value of 31 HU. Thirty-four cases of adrenal hormones were evaluated, and no abnormality was found.The primary tumor sites were as follows: lung (n=36), kidney (n=19), liver (n=12), pancreas (n=7), rectum (n=3), stomach (n=2), and one case each of tumor in the esophagus, skin, thyroid, left maxillary muscle, breast, bladder, cervix, chest wall, and gastrointestinal tract. There were three cases with unknown primary tumors. The most common pathological type was lung adenocarcinoma (20.8%, 20/96), followed by hepatocellular carcinoma (9.4%, 9/96) and high-grade invasive urothelial carcinoma of the kidney (8.3%, 8/96). Thirty-nine cases were diagnosed concurrently with the primary tumor, while 37 cases were diagnosed after the primary tumor, with a median interval of 15 months (range: 2-144 months). There was no significant correlation between the death risk of adrenal metastatic tumor patients and gender, age, and the size of the metastatic tumor (all P>0.05). There were 4 patients with radiotherapy and chemotherapy alone, 19 patients with surgery alone, and 6 patients with combined radiotherapy and chemotherapy. The median overall survival was 1, 3, and 7 years, respectively. Conclusions: Adrenal metastases were mostly diagnosed at the same time as the primary tumor or within 15 months after the diagnosis of the primary tumor. Unilateral metastasis is common. The lungs are the most common primary lesion, followed by the kidney and liver. CT is the preferred method for the diagnosis of adrenal metastases, and the plain CT value is more than 30 HU. The overall prognosis of adrenal metastases is poor. The prognosis was better for patients who underwent surgery combined with radiotherapy and chemotherapy than those who received only surgery or radiotherapy and chemotherapy alone.

Contrast enhancement boost improves the image quality of CT angiography derived from 80-kVp cerebral CT perfusion data

Rationale and objectiveTo investigate the impact of the contrast enhancement boost (CE-boost) technique on the image quality of CT angiography (CTA) derived from 80-kVp cerebral CT perfusion (CTP) data, and to compare it with conventional CTApeak as well as other currently employed methods for enhancing CTA images, such as CTAtMIP and CTAtAve extracted from CTP.Materials and methodsThe data of forty-seven patients who underwent CTP at 80 kVp were retrospectively collected. Four sets of images: CTApeak, CTAtMIP, CTAtAve, and CE-boost images. The CTApeak image represents the arterial phase at its peak value, captured as a single time point. CTAtMIP and CTAtAve are 4D CTA images that provide maximum density projection and average images from the three most prominent time points. CE-boost is a postprocessing technique used to enhance contrast in the arterial phase at its peak value. We compared the average CT value, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the internal carotid artery (ICA) and basilar artery (BA) among the four groups. Image quality was evaluated using a 5-point scale.ResultsThe CE-boost demonstrated and CNR in the ICA and BA (all p < 0.001). Compared with the other three CTA reconstructed images, the CE-boost images had the best subjective image quality, with the highest scores of 4.77 ± 0.43 and 4.87 ± 0.34 for each reader (all p < 0.001).ConclusionCompared with other currently used techniques,CE-boost enhances the image quality of CTA derived from 80-kVp CTP data, leading to improved visualization of intracranial arteries.

The effect of vaccination of gilts with a pre-farrow RNA particle vaccine following pre-breeding natural planned exposure on piglet growth and viral shedding

The objective of this study was to compare rotavirus shedding and performance of piglets from gilts immunized using natural planned exposure (NPE) or an RNA particle vaccine (RPV) prior to farrowing following initial NPE pre-breeding. A final total of 117 farrowed gilts and their piglets were enrolled into 4 groups. All gilts received two administrations of NPE prior to breeding. Gilts in group 1 were later given three NPE administrations at 5, 4, and 3 weeks prior to farrowing (WPF). Group 2 was dosed with an RNA particle vaccine (RPV) at 5 and 3 WPF and group 3 at 1 WPF only. Group 4 (control group) did not receive any NPE or RPV. Fecal samples from gilts and fecal swabs from their piglets were tested for rotavirus A (RVA), rotavirus B (RVB), and rotavirus C (RVC) by qRT-PCR. The 117 gilt samples were tested individually at 5 sampling points from pre-breeding to entry into the farrowing rooms. Piglet samples were pooled by litter (3 piglets sampled per litter) and tested at 3, 7, 14, and 21 days of age. The clinical and production impact of the treatments were assessed by comparing average adjusted weaning weights, the percentage of piglets weighing in the bottom 10% of study piglets at weaning, the percentage of piglets placed in the nursery, and the percentage of litters with the presence of diarrhea. No statistically significant differences were identified but there appeared to be several interesting numerical trends that are both biologically plausible and consistent among treatment groups. The control group, which received no pre-farrow immunization, had the highest percentage of litters with diarrhea at all time points and overall in the farrowing house. A numerical trend was also observed on average cycle threshold (Ct) values for RVC in piglets. Interestingly, the control group had the lowest numerical average Ct value at 7, 14, and 21 days of age. Ct values for RVA were consistently lower than for RVC in the stock solution and natural planned exposure gruel. This likely correlated to a lower level of RVC exposure in all gilts pre-breeding and group 1 gilts pre-farrow. This may have an inverse correlation to the higher levels of shedding of RVC in piglets. The lack of statistical significance between treatment groups with regard to diarrhea and weights in the piglets may be attributed to sample size, lack of sufficient natural rotavirus challenge, pre-breeding NPE in all gilts, or a variety of other reasons. Replication of this study with a larger sample size, using a challenge model, or relocated to a farm with increased natural rotavirus clinical challenges may yield different results. If beneficial under different conditions, the RPV would eliminate many of the risks associated with NPE administration, including continuous introduction of live virus on-farm, potential spread of other pathogens, difficulty of isolating on-farm strains, and labor and cost of producing NPE material. Limitations of the original research include the use of quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) to measure the levels of RVA and RVC in the stock solution and gruel and to monitor RV shedding, rather than techniques with the ability to differentiate live and non-viable virus. Additionally, these studies were performed on an all-gilt breeding farm. It may be more challenging to appreciate differences in treatment groups on a multiparous sow farm due to the higher level of immunity correlated to increasing parity. These immunization protocols were designed to be applicable in a field setting for routine rotavirus immunization, though their feasibility must be carefully considered before implementation on each individual farm.

First detection of PCV4 in swine in the United States: codetection with PCV2 and PCV3 and direct detection within tissues

Since PCV4 was first described in 2019, the virus has been identified in several countries in Southeast Asia and Europe. Most studies have been limited to detecting PCV4 by PCR. Thus, PCV4 has an unclear association with clinical disease. This study utilized 512 porcine clinical lung, feces, spleen, serum, lymphoid tissue, and fetus samples submitted to the ISU-VDL from June–September 2023. PCV4 was detected in 8.6% of samples with an average Ct value of 33. While detection rates among sample types were variable, lymphoid tissue had the highest detection rate (18.7%). Two ORF2 sequences were obtained from lymphoid tissue samples and had 96.36–98.98% nucleotide identity with reference sequences. Direct detection of PCV4 by RNAscope revealed viral replication in B lymphocytes and macrophages in lymph node germinal centers and histiocytic and T lymphocyte infiltration in the lamina propria of the small intestine. PCV4 detection was most commonly observed in nursery to finishing aged pigs displaying respiratory and enteric disease. Coinfection with PCV2, PCV3, and other endemic pathogens was frequently observed, highlighting the complex interplay between different PCVs and their potential roles in disease pathogenesis. This study provides insights into the frequency of detection, tissue distribution, and genetic characteristics of PCV4 in the US.

A Treatise about Some Anomalous Laboratory Investigation Results Accompanying HLA-B27 Positive Higher Age Group Population

HLA-B27 test is generally positive in spondyloarthritis (SpA) and ankylosing spondylitis (AS). Several anomalous laboratory test results are frequently found in HLA-B27-positive patients. In this study, we intended to evaluate two groups of HLA-B27 positive patients- one group belonging to the 13-40 years age group and another group belonging to the 41-71 years age group. The rationale of this partition was based on the age when AS first emerged and the age when the disease was set up for quite a few years respectively. We anticipate alterations of several familiar laboratory test outcomes between these two groups. After our analysis, we found that in the upper age group, neutrophil percentage and CRP levels were significantly increased, while lymphocyte percentage was significantly decreased. ESR levels also decreased but were not statistically significant. There was practically no change in average PCR ct values, haemoglobin levels, total count of leucocytes, uric acid, creatinine, SGPT, or HbA1C levels between the two groups. The plausible explanations behind these changes are discussed.

Application value of the automated machine learning model based on modified CT index combined with serological indices in the early prediction of lung cancer.

Accurately predicting the extent of lung tumor infiltration is crucial for improving patient survival and cure rates. This study aims to evaluate the application value of an improved CT index combined with serum biomarkers, obtained through an artificial intelligence recognition system analyzing CT features of pulmonary nodules, in early prediction of lung cancer infiltration using machine learning models. A retrospective analysis was conducted on clinical data of 803 patients hospitalized for lung cancer treatment from January 2020 to December 2023 at two hospitals: Hospital 1 (Affiliated Changshu Hospital of Soochow University) and Hospital 2 (Nantong Eighth People's Hospital). Data from Hospital 1 were used for internal training, while data from Hospital 2 were used for external validation. Five algorithms, including traditional logistic regression (LR) and machine learning techniques (generalized linear models [GLM], random forest [RF], gradient boosting machine [GBM], deep neural network [DL], and naive Bayes [NB]), were employed to construct models predicting early lung cancer infiltration and were analyzed. The models were comprehensively evaluated through receiver operating characteristic curve (AUC) analysis based on LR, calibration curves, decision curve analysis (DCA), as well as global and individual interpretative analyses using variable feature importance and SHapley additive explanations (SHAP) plots. A total of 560 patients were used for model development in the training dataset, while a dataset comprising 243 patients was used for external validation. The GBM model exhibited the best performance among the five algorithms, with AUCs of 0.931 and 0.99 in the validation and test sets, respectively, and accuracies of 0.857 and 0.955 in the validation and test groups, respectively, outperforming other models. Additionally, the study found that nodule diameter and average CT value were the most significant features for predicting lung cancer infiltration using machine learning models. The GBM model established in this study can effectively predict the risk of infiltration in early-stage lung cancer patients, thereby improving the accuracy of lung cancer screening and facilitating timely intervention for infiltrative lung cancer patients by clinicians, leading to early diagnosis and treatment of lung cancer, and ultimately reducing lung cancer-related mortality.

Laboratory Results and Clinical Characteristics of Probable Omicron Patients at Dr. Wahidin Sudirohusodo Hospital

Since the Omicron variant was first detected on November 24, 2021, in Southern Africa, it has now been detected in more than 110 countries and is estimated to continue to spread. Given the rapid spread and serious dangers of COVID-19, it is urgent to continuously improve and expand research on its clinical diagnosis and treatment. The analysis of this study identifies the laboratory results and clinical characteristics of probable Omicron. This study aimed to determine the laboratory results and clinical characteristics of probable Omicron patients at Dr. Wahidin Sudirohusodo Hospital. This descriptive study used a cross-sectional approach with medical record data of probable Omicron patients at Dr. Wahidin Sudirohusodo Hospital from January to July 2022 with a total of 241 research subjects. The results of the analysis showed that probable Omicron patients at Dr. Wahidin Sudirohusodo Hospital who were hospitalized consisted of 124 (51.5%) males and 117 (48.5%) females, 66 (22.8%) subjects with age range &gt;60 years, 88 (30.4%) subjects with age range of 40-60 years, 45 (15.6%) subjects with age range 19-40 years and 42 (14.5%) subjects with age &lt;18. Most subjects, which consisted of 79 (27.3%) patients reside in Makassar. The mean WBC count, NLR value, LMR value, and CT value found in this study were 10.8; 5.6; 0.5; and 33.94, respectively. The Omicron variant infects more males than females mainly at the age of 40-60 years, with a relatively low average CT value of 33.94 and a slight increase of NLR, MLR, and WBC count.

Analysis of clinicopathologic and imaging features of dual-phenotype hepatocellular carcinoma

Dual-phenotype hepatocellular carcinoma (DPHCC) is a new subtype of hepatocellular carcinoma (HCC). This study aimed to investigate the relationship between the computerized tomography scan (CT) imaging and clinicopathologic features of DPHCC. The CT imaging and clinicopathologic data of 97 HCC cases who underwent radical resection were collected retrospectively. The CT imaging feature was evaluated by the ratio of the average CT value of tumor to liver (TLR) in the plain scan, arterial, portal vein and delayed phases. The association between CT imaging and clinicopathologic features was analyzed using the t-test or chi-square test. Univariate and multivariate recurrence-free survival (RFS) analysis and overall survival (OS) were performed. The positive rates of cytokeratin 7 (CK7) and CK19 were 35.1% and 20.6% respectively. The positive rate of CK19 was significantly higher in cases with age < 47 years (P = 0.005), tumor diameter > 4 cm (P = 0.016) or AFP ≥ 400 ng/ml (P = 0.007). The TLR in the portal vein phase was significantly lower in CK19 positive group (P = 0.024). The recurrence risk was significantly higher in cases with CK19 positive (HR: 2.17, 95% CI 1.16 to 4.04, P = 0.013), tumor diameter > 4 cm (HR: 2.05, 95% CI 1.11 to 3.78, P = 0.019), AFP ≥ 400 ng/ml (HR: 2.50, 95% CI 1.37 to 4.54, P = 0.002) or CA199 ≥ 37 U/ml (HR: 2.23, 95% CI 1.12 to 4.42, P = 0.020). However, imaging features, pathological subtype, CK7 or CK19 expression were not significantly related to HCC OS in the univariate and multivariate analysis (all P > 0.05). The expression of CK19 may be associated with the enhancement feature of the portal vein phase CT image, and CK19 positive may suggest a worse RFS.

Experimental study on determining the degree of bone healing by wall thickness ratio analysis

To verify the reliability and accuracy of wall thickness ratio analysis to determine the degree of bone healing, fracture models were established with 6 beagles. X-ray, micro-CT, and CT scans were performed at 24 weeks. The healthy side and the affected side were used to simulate the three-dimensional geometric model after internal fixation, and the mesh was divided. The mean and median CT wall thickness values were obtained through the wall thickness analysis. X-ray, CT, micro-CT, and gross appearance were used to determine the degree of bone healing, which was compared with wall thickness analysis. There was a positive correlation between the average CT value and the median wall thickness. The correlation coefficient analysis of the median wall thickness ratio (R2) and healing index ratio (R3) showed a positive correlation. The results of the wall thickness ratio (R2) and the healing index ratio (R3) were used to determine bone healing, and the results were consistent with the results of the actual mechanical test and image analysis. The results of wall thickness ratio analysis were significantly correlated with the degree of bone healing. This method is simple, rapid, and practical to analyze and judge the degree of bone healing.

Epidemiological survey of elderly patients diagnosed with COVID-19 at mobile field hospitals.

During the COVID-19 pandemic, the mobile field hospital, a rapidly deployable healthcare facility for emergency care, was effective in ensuring rapid diagnosis and treatment of patients with mild or asymptomatic SARS-CoV2 infections, effectively preventing the spread of COVID-19. We conducted a survey to gain a thorough understanding of the epidemiological traits among the elderly who contracted the Omicron variant of the SARS-CoV-2 virus at a mobile field hospital set up at the National Exhibition and Convention Center (Shanghai). A cross-sectional study approach was employed to examine various factors such as demographic characteristics, clinical features, vaccination status, and nucleic acid testing. We utilized the DezhenTech Integrated Electronic Medical Record Platform (Municipal Isolation Hospital) to collect data and focused on elderly individuals infected with COVID-19 in the fifth isolation zone of the mobile field hospital set up at the National Exhibition and Convention Center (Shanghai). The patients were categorized into different age groups for analysis. Among the 3,183 elderly patients, 54.7% were males and 45.3% were females, with an average age of 65.32 ± 4.41years. Among them, 47.8% (1523/3183) were 60-64 years old, 34.0% (1082/3183) were 65-69 years old, 14.0% (444/3183) were 70-74 years old, 3.2% (103/3183) were 75-79 years old, and 1.0% (31/3183) were ⩾ 80 years old. The majority (95.7%) of the elderly patients with chronic conditions had hypertension, diabetes, and coronary heart disease. The first viral nucleic acid screening showed a higher positive rate in the community and hospital fever clinics. The cumulative positive rate of the nucleic acid test in the mobile field hospital was 38.7%. The average CT value of the COVID-19 ORF1ab gene was 34.56 ± 5.98, while the average CT value of the N gene was 33.10 ± 6.50. The patients took an average of 3.40 ± 0.45 days to test negative, with a positive rate of 15.4% and an average hospital stay of 7.45 ± 0.53 days. The overall rate of COVID-19 vaccine coverage was 68.0%, with an enhanced coverage rate of 40% and a non-coverage rate of 29.3%. The overall prognosis for elderly patients who experienced a mild or asymptomatic SARS-CoV-2 Omicron infection at the mobile field hospital was favorable, although the vaccination rate in general was not high. By effectively managing underlying health conditions, the duration of their hospital stay in the mobile field hospital was reduced.

Comparison of a novel rapid sampling method to serum and tonsil scraping to detect PRRSV in acutely infected sows

Few practical methods are available to monitor the PRRSV status of the sows. Common sampling methods for sows like serum sampling, and tonsil scraping involve restraining individual sows and are labor-intensive, time-consuming, relatively invasive, and therefore, have limited use in large-scale production settings. Thus, a practical and rapid method of sampling large numbers of sows is needed. This study aimed to develop a new sampling method, named tonsil-oral scraping (TOSc) and compare TOSc to serum and tonsil scraping in terms of PRRSV qPCR detection rate and Ct values in thirty matched sows, thirty days after PRRSV outbreak. TOSc recovered a mixture of oral fluids and tonsil exudates from the sow oral cavity within seconds without restraining the animals. Results showed that, numerically, the TOSc samples had higher PRRSV qPCR detection rate (100 %) compared to serum (16.8 %) and tonsil scraping (73.1 %). Moreover, TOSc samples had lower average Ct values (29.7) than tonsil scraping (30.7) and serum (35.2). There was no significant difference in the detection rate between TOSc and tonsil scraping (Tukey test, p = 0.992), while there was a significant difference between serum and tonsil scraping (Tukey test, p < 0.001), as well as between serum and TOSc (Tukey test, p < 0.001). In terms of Ct values, there was no statistically significant difference between TOSc and tonsil scrapings (Dunn Test, p > 0.05), while there was a significant difference between tonsil scraping with serum (Dunn Test, p < 0.01), and TOSc with serum (Dunn Test, p < 0.01). Our results suggest great potential of the TOSc as a novel, practical, and rapid tool for PRRSV RNA detection in sows to assess sow herd status.

SARS-CoV-2 testing in the Slovak Republic from March 2020 to September 2022 - summary of the pandemic trends.

The COVID-19 pandemic has been part of Slovakia since March 2020. Intensive laboratory testing ended in October 2022, when the number of tests dropped significantly, but the state of the pandemic continues to this day. For the management of COVID-19, it is important to find an indicator that can predict pandemic changes in the community. The average daily/weekly Ct value with a certain time delay can predict changes in the number of cases of SARS-CoV-2 infection, which can be a useful indicator for the healthcare system. The study analyzed the results of 1,420,572 RT-qPCR tests provided by one accredited laboratory during the ongoing pandemic in Slovakia from March 2020 to September 2022. The total positivity of the analyzed tests was 24.64%. The average Ct values found were the highest in the age group of 3-5 years, equal to the number 30.75; the lowest were in the age group >65 years, equal to the number 27. The average weekly Ct values ranged from 22.33 (pandemic wave week) to 30.12 (summer week). We have summarized the results of SARS-CoV-2 diagnostic testing in Slovakia with the scope defined by the rate and positivity of tests carried out at Medirex a.s. laboratories.

Next-Generation Sequencing of microRNAs in Small Abdominal Aortic Aneurysms: MiR-24 as a Biomarker

Small abdominal aortic aneurysms (AAAs) are asymptomatic but can potentially lead to rupture if left undetected. To date, there is a lack of simple nonradiologic routine tests available for diagnosing AAAs. MicroRNAs (miRNAs) have been proven to be good-quality biomarkers in several diseases, including AAA. An attempt to identify a panel of circulating miRNAs with differential expression in AAAs via next-generation sequencing (NGS) was performed in serum samples: small AAAs (n=3), large AAAs (n=3), and controls (n=3). For miR-24, validation with real-time polymerase chain reaction (PCR) was undertaken in a larger group (n=80). In the NGS study, 23 miRNAs were identified as differentially expressed (with statistical significance) in small AAAs in comparison with controls. Among them, miR-24 showed the largest upregulation with 23-fold change (log2FC 4.5, P=0.024). For large AAAs compared with controls, and small AAAs compared with large AAAs, a panel of 33 and 131 miRNAs showed statistically significant differential expression, respectively. Based on the results of the NGS stage, a literature search was performed, and information regarding AAA pathogenesis, coronary artery disease, and peripheral arterial disease was documented where applicable: miR-24, miR-103, miR-193a, miR-486, miR-582, and miR-3663. Of these 6 miRNAs, miR-24 was chosen for further validation with real-time PCR. Additionally, in the NGS study analysis, 17 miRNAs were common between the small-large AAAs, small AAAs-controls, and large AAAs-controls comparisons: miR-7846, miR-3195, miR-486-2, miR-3194, miR-5589, miR-1538, miR-3178, miR-4771-1, miR-5695, miR-6504, miR-1908, miR-6823, miR-3159, miR-23a, miR-7853, miR-496, and miR-193a. Interestingly, in the validation stage with real-time PCR, miR-24 was found downregulated in small and large AAAs compared with controls (fold-changes: 0.27, P=0.015 and 0.15, P=0.005, respectively). No correlation was found between average Ct values, aneurysm diameter, and patients' age. Our findings further highlight the importance of miR-24 as a potential biomarker as well as a therapeutic target for abdominal aneurysmal disease. Future research and validation of a panel of miRNAs for AAA would aid in diagnosis and discrimination between diseases with overlapping pathogeneses.

Clinical Study of Artificial Intelligence in Imaging Diagnosis of False Positive Lesions of Pulmonary Nodules.

To determine the accuracy of diagnosis of pulmonary nodules using artificial intelligence method. Observational study. Place and Duration of the Study: Department of Thoracic Surgery, Jinan Central Hospital, Jinan, China, from January 2020 to May 2021. An analysis of clinical characteristics exhibited by 32 patients initially diagnosed with malignant tumours through imaging (LDCT) and artificial intelligence (AI), was reclassified as having benign lesions following surgical intervention. Quantitative parameters were assessed, including CT mean value, kurtosis, skewness, solid ratio, and the ratio of length to short diameter, within a cohort of 32 benign patients juxtaposed with 58 patients diagnosed with lung cancer during the same time frame. The AI-derived parameters were subjected to Mann-Whitney U non-parametric test. A total of 32 benign pulmonary lesions were evaluated that were initially misdiagnosed as malignant prior to surgery. These lesions displayed an average length of (18.56 ± 12.16) mm, with the majority characterised as solid (68.8%). Notably, a substantial proportion of these lesions exhibited imaging features akin to malignant growths. The AI-derived quantitative parameters of the 32 benign cases and the 58 malignant cases revealed statistical significance in average CT value and solid ratio. However, statistical significance was not established for kurtosis, skewness, or the ratio of length to short diameter. The area under the Receiver Operating Characteristic (ROC) curve for average CT value and solid ratio stood at 0.71 and 0.705, respectively. Among the cases initially misdiagnosed as malignant yet subsequently identified as benign, a notable number of these instances were solid nodules, often resembling malignant lesions in imaging characteristics. There was moderate discriminatory capacity for average CT value and solid ratio, rendering them valuable tools for distinguishing between benign and malignant lesions within this particular cohort. This underscores their high diagnostic significance. Artificial intelligence, Benign lesions of lung, Lung cancer, Quantitative parameters, Postoperative.

Screening for osteoporosis based on IQon spectral CT virtual low monoenergetic images: Comparison with conventional 120 kVp images

ObjectivesTo explore the differences between low kiloelectron volt (keV) virtual monoenergetic images (VMIs) using IQon spectral CT and conventional CT (120 kVp) in the diagnosis of osteoporosis. MethodsThis retrospective study included 317 patients who underwent IQon spectral CT and dual-energy X-ray absorptiometry (DXA) examination. Commercial deep learning–based software was used for the fully automated extraction of the CT values of the first to fourth lumbar vertebrae (L1–L4) from two different low-keV levels (including 40/70 keV) VMIs and conventional 120 kVp images. The DXA examination results served as the standard of reference (normal [T-score ≥ −1], osteopenia [-2.5 < T-score < −1], and osteoporosis [T-score < −2.5]). Osteoporosis diagnosis models were constructed using machine learning classifiers (logistic regression, support vector machine, random forest, XGBoost, and multilayer perceptron) based on the average CT values of L1–L4. The area under the receiver operating characteristic curve (AUC) and DeLong test were performed to compare differences in the performance of the osteoporosis diagnosis model between virtual low-keV VMIs and standard 120 kVp images. ResultsRandom forest-based prediction model obtained good overall performance among all classifiers, and macro/micro average AUC values of 0.820/840, 0.834/853, and 0.831/852 were obtained based on 40/70 keV and 120 kVp images, respectively. The model presented no significant difference between low-keV VMIs and standard 120 kVp images for the diagnosis of osteoporosis (p > 0.05). ConclusionsThe performance of the osteoporosis diagnosis model using IQon spectral CT simulating the low tube voltage scanning condition (less than 120 kVp) was also satisfactory. Bone density screening evaluation can be performed with a combination of low-dose lung scanning CT, greatly reducing the radiation dose without affecting the diagnosis.

Validation of deep learning-based CT image reconstruction for treatment planning

Deep learning-based CT image reconstruction (DLR) is a state-of-the-art method for obtaining CT images. This study aimed to evaluate the usefulness of DLR in radiotherapy. Data were acquired using a large-bore CT system and an electron density phantom for radiotherapy. We compared the CT values, image noise, and CT value-to-electron density conversion table of DLR and hybrid iterative reconstruction (H-IR) for various doses. Further, we evaluated three DLR reconstruction strength patterns (Mild, Standard, and Strong). The variations of CT values of DLR and H-IR were large at low doses, and the difference in average CT values was insignificant with less than 10 HU at doses of 100 mAs and above. DLR showed less change in CT values and smaller image noise relative to H-IR. The noise-reduction effect was particularly large in the low-dose region. The difference in image noise between DLR Mild and Standard/Strong was large, suggesting the usefulness of reconstruction intensities higher than Mild. DLR showed stable CT values and low image noise for various materials, even at low doses; particularly for Standard or Strong, the reduction in image noise was significant. These findings indicate the usefulness of DLR in treatment planning using large-bore CT systems.