Electronic Nose and Tongue for Assessing Human Microbiota

Vitamin D: An Essential Nutrient in the Dual Relationship between Autoimmune Thyroid Diseases and Celiac Disease-A Comprehensive Review

Autoimmune thyroid diseases (AITD) are among the most frequent autoimmune disorders, with a multifactorial etiology in which both genetic and environmental determinants are probably involved. Celiac disease (CeD) also represents a public concern, given its increasing prevalence due to the recent improvement of screening programs, leading to the detection of silent subtypes. The two conditions may be closely associated due to common risk factors, including genetic setting, changes in the composition and diversity of the gut microbiota, and deficiency of nutrients like vitamin D. This comprehensive review discussed the current evidence on the pivotal role of vitamin D in modulating both gut microbiota dysbiosis and immune system dysfunction, shedding light on the possible relevance of an adequate intake of this nutrient in the primary prevention of AITD and CeD. While future technology-based strategies for proper vitamin D supplementation could be attractive in the context of personalized medicine, several issues remain to be defined, including standardized assays for vitamin D determination, timely recommendations on vitamin D intake for immune system functioning, and longitudinal studies and randomized controlled trials to definitely establish a causal relationship between serum vitamin D levels and the onset of AITD and CeD.

Perylene diimide-based sensors for multiple analyte sensing (Fe2+/H2S/ dopamine and Hg2+/Fe2+): cell imaging and INH, XOR, and encoder logic

In this report, we present our results on the recognition of multiple analytes using trisubstituted PDI-based chemosensors DNP and DNB in 50% HEPES buffered-CH₃CN solution. Upon the addition of Hg²⁺, DNB showed a decrease and increase in absorbance intensity at 560 and 590 nm, respectively, with a detection limit of 7.17 μM and bleaching of the violet color (de-butynoxy). Similarly, the addition of Fe²⁺ or H₂S to the solution of DNP or DNB resulted in ratiometric changes (A_688nm/A_560nm) with respective detection limits of 185 nM and 27.6 nM for Fe²⁺, respectively, and a color change from violet to green. However, the addition of >37 μM H₂S caused a decrease in absorbance at 688 nm with a concomitant blue shift to 634 nm. Upon the addition of dopamine, the DNP + Fe²⁺ assay showed ratiometric (A_560nm/A_688nm) changes within 10 s along with a color change from green to violet. Moreover, DNP has been successfully used for the exogenous detection of Fe²⁺ in A549 cells. Further, the multiple outputs observed with DNP in the presence of H₂S have been used to construct NOR, XOR, INH and 4-to-2 encoder logic gates and circuits.

Evaluation of an AI-Based TB AFB Smear Screening System for Laboratory Diagnosis on Routine Practice

The most robust and economical method for laboratory diagnosis of tuberculosis (TB) is to identify mycobacteria acid-fast bacilli (AFB) under acid-fast staining, despite its disadvantages of low sensitivity and labor intensity. In recent years, artificial intelligence (AI) has been used in TB-smear microscopy to assist medical technologists with routine AFB smear microscopy. In this study, we evaluated the performance of a TB automated system consisting of a microscopic scanner and recognition program powered by artificial intelligence and machine learning. This AI-based system can detect AFB and classify the level from 0 to 4+. A total of 5930 smears were evaluated on the performance of this automatic system in identifying AFB in daily lab practice. At the first stage, 120 images were analyzed per smear, and the accuracy, sensitivity, and specificity were 91.3%, 60.0%, and 95.7%, respectively. In the second stage, 200 images were analyzed per smear, and the accuracy, sensitivity, and specificity were increased to 93.7%, 77.4%, and 96.6%. After removing disqualifying smears caused by poor staining quality and smear preparation, the accuracy, sensitivity, and specificity were improved to 95.2%, 85.7%, and 96.9%, respectively. Furthermore, the automated system recovered 85 positive smears initially identified as negative by manual screening. Our results suggested that the automated TB system could achieve higher sensitivity and laboratory efficiency than manual microscopy under the quality control of smear preparation. Automated TB smear screening systems can serve as a screening tool at the first screen before manual microcopy.