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Fluorescence imaging-assisted thoracoscopic anatomical lesion resection in treating congenital lung malformation

ADAMDEC1 promotes the malignant progression of cholangiocarcinoma by regulating NF-κB signaling pathway

Soft grid integration control strategy for self synchronized voltage source DFIG wind turbine generator

Self-compassion as a mediator of attachment anxiety, attachment avoidance, and complex PTSD in college students with adverse childhood experiences

Conceptual foundations of a REFRAME-based approach to discriminate across total knee implant designs based on the positions of functional centres of rotation

Quantitative risk assessment of rainstorm-induced flood disaster in Piedmont plain of Pakistan

Computational evaluation of micropores wetting effect on the removal process of CO2 through the membrane contactor

A disintegrin and metallopeptidase domain (ADAM) 12, ADAM 17 mRNA and ADAM10 protein hold potential as biomarkers for detection of early gastric cancer

AbstractNo biomarker can effectively screen for early gastric cancer (EGC). Players in the A disintegrin and metalloproteinase (ADAM)-natural killer group 2 member D (NKG2D) receptor axis may have a role for that. As a proof-of-concept pilot study, the expression of ADAM8, ADAM9, ADAM10, ADAM12, ADAM17, and major histocompatibility complex (MHC) class I chain-related sequence A (MICA), a ligand for NKG2D, in gastric cancer was investigated in silico using The Cancer Genome Atlas (TCGA) database. Subsequently, the mRNA and protein expression levels of these markers except ADAM8 were tested in blood samples from patients with EGC and healthy controls. In the TCGA data analyses, EGC tissues (n = 57) expressed significantly higher mRNA levels of ADAM8, ADAM9, ADAM10, ADAM12, and ADAM17 than normal tissues (n = 35) (p < 0.005). In human blood sample analyses, ADAM12 (p = 0.0007), ADAM17 mRNA (p < 0.0001) and ADAM10 (p < 0.0017) protein were significantly elevated in patients with EGC (n = 27 for mRNA and n = 25 for protein) compared to the controls (n = 30 for mRNA and n = 26 for protein). Areas under the curves calculated by receiver-operating characteristic analysis for ADAM12, ADAM17 mRNA and ADAM10 protein were 0.7568 (95% confidence interval [CI]: 0.6334 to 0.8802), 0.8062 (95% CI: 0.6889 to 0.9234; p < 0.0001), and 0.8108 (95% CI: 0.6895 to 0.9320; p = 0.0001), respectively. Thus, ADAM12, ADAM17 mRNA and ADAM10 protein levels in peripheral blood could hold potential as biomarkers for screening EGC, and further investigations are required.

Cystoid macular oedema after flanged intraocular lens scleral fixation using the Yamane technique: a multicentre cohort study

Development of lateral flow immunochromatographic assay with Anti-Pythium insidiosum antibodies for point-of-care testing of vascular pythiosis

Prediction of pulmonary embolism by an explainable machine learning approach in the real world

Spillover effect of children’s education on parental physical functioning over the life course

Mendelian randomization analysis reveals causal relationship between depression, antidepressants and benign paroxysmal vertigo

Complex Diophantine interval-valued Pythagorean normal set for decision-making processes

Nanobody-based indirect competitive ELISA for the detection of aflatoxin M1 in dairy products

AbstractAflatoxin M1 (AFM1) is known to be carcinogenic, mutagenic, and teratogenic and poses a serious threat to food safety and human health, which makes its surveillance critical. In this study, an indirect competitive ELISA (icELISA) based on a nanobody (Nb M4) was developed for the sensitive and rapid detection of AFM1 in dairy products. In our previous work, Nb M4 was screened from a Bactrian-camel-immunized phage-displayed library. It exhibits VH-like features, possesses higher thermal stability than monoclonal antibody (mAb 1E6) and tightly binds to AFM1–BSA with a KD value of 2.5 nM. Under the optimal conditions, its half-maximal inhibitory concentration was 0.338 ng/mL, the limit of detection was 0.051 ng/mL, and linearity was noted in the range of 0.168–0.679 ng/mL. Nb M4 displayed almost no cross-reactivity with other mycotoxins. No matrix effect was observed in milk and milk powder samples, and the matrix effect in yogurt samples could be weakened by 2-fold dilution. Furthermore, validation studies in spiked samples (milk, yogurt, and milk powder) resulted in good recoveries of 95.40–111.33%, with a low coefficient of variation (2.89–6.78%). High-performance liquid chromatography was used to evaluate the accuracy and reliability of the developed icELISA, which indicated a satisfactory consistent correlation (R2 = 0.9722). This study highlights the potential of Nb M4 as a promising component for detecting AFM1 in dairy products.

Sleep deprivation and corneal chronobiology: reevaluating overnight corneal changes

AbstractThis prospective cohort study is aimed to investigate circadian variations in corneal parameters, focusing on sleep-deprived subjects. Sixty-four healthy individuals (age range: 21–76 years) actively participated in this study, undergoing examinations at least five times within a 24-hour timeframe. The analysis encompassed keratometric parameters of the cornea’s front (F) and back (B) surfaces, refractive power in flattest and steepest axes (K1, K2), astigmatism (Astig) and its axis (Axis), aspheric coefficient (Asph), corneal pachymetry values of thinnest corneal thickness (Pachy Min) and corneal thickness in the center of the pupil (Pachy Pupil), volume relative to the 3 and 10 mm corneal diagonal (Vol D3, Vol D10) and surface variance index (ISV). Circadian changes were assessed using a hierarchical, mixed-effects linear regression adjusted for age and night shift. A total of 1,636 measurements revealed significant circadian changes in various corneal parameters, including K1 F, K2 F/B, Astig F/B, Asph F/B, Pachy Min/Pupil, Vol D3/10, and ISV (p < 0.0001). Moreover, K1 B exhibited a significant circadian change (p = 0.0002), while Axis F/B remained unchanged. Notably, Corneal thickness peaked before 6 o’clock in the morning and reached its minimum after 12 o’clock. Contrary to previous notions linking corneal diurnal changes with eyelid closure during sleep, our study reveals that these changes persist in the absence of sleep. This research contributes valuable insights into the impact of sleep deprivation on corneal properties, warranting further investigations to deepen our understanding of daily variations in visual quality and guide the planning of refractive eye surgery interventions.

Rectal glands and tergal glands as sources of volatile pheromones in cucumber fruit fly, Zeugodacus Cucumis

A preliminary exploration of establishing a mice model of hypoxic training

Puerarin pretreatment provides protection against myocardial ischemia/reperfusion injury via inhibiting excessive autophagy and apoptosis by modulation of HES1

Electrical impedance-based tissue classification for bladder tumor differentiation

AbstractIncluding sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove. Over the years of research, it became obvious that electrical impedance spectroscopy is a very promising tool for tissue differentiation, but also a very sensitive one. While differentiation in preliminary studies shows great potential, challenges arise when transferring this concept to real, intraoperative conditions, mainly due to the influence of preoperative radiotherapy, possibly different tumor types, and mechanical tissue deformations due to peristalsis or unsteady contact force of the sensor. This work proposes a patient-based classification approach that evaluates the distance of an unknown measurement to a healthy reference of the same patient, essentially a relative classification of the difference in impedance that is robust against inter-individual differences and systematic errors. A diversified dataset covering multiple disturbance scenarios is recorded. Two alternatives to define features from the impedance data are investigated, namely using measurement points and model-based parameters. Based on the distance of the feature vector of a unknown measurement to a healthy reference, a Gaussian process classifier is trained. The approach achieves a high classification accuracy of up to 100% on noise-free impedance data recorded under controlled conditions. Even when the differentiation is more ambiguous due to external disturbances, the presented approach still achieves a classification accuracy of 80%. These results are a starting point to tackle intraoperative bladder tissue characterization and decrease the recurrence rate.