Prediction of necrotizing enterocolitis in very low birth weight infants by superior mesenteric artery ultrasound of postnatal day 1: A nested prospective study

BackgroundNecrotizing enterocolitis (NEC) is a devastating intestinal complication that occurs mainly in very-low-birth-weight infants (VLBWI). The study's aim was to investigate the possibility of early prediction of NEC on postnatal day 1 based on superior mesenteric artery (SMA) doppler ultrasonograpy.MethodsA prospective, observational, nested case control study (ChiCTR1900026197) was conducted to enroll VLBWIs (birth weight <1,500 grams) between October 2019 and September 2021. Doppler ultrasound measurement was done during the first 12 h of life and before first feeding. Infants developing NEC (stage II or III) subsequently were included in NEC group and infants spare of NEC were included in control group.Results370 VLBWIs were enrolled (30 NEC cases). Among the ultrasound parameters, S/D was significantly higher in the NEC group (OR: 2.081, 95% CI: 1.411–3.069, P = 0.000). The area under the receiver operating curve (AUROC) following the Logistic regression was 0.704 (95% CI: 0.566–0.842, P = 0.001). The sensitivity of S/D for predicting NEC was 52.2% and the specificity was 92.7%. The critical value of S/D was 6.944 and Youden index was 0.449. Preplanned subgroup analysis confirmed that NEC infants of different stages were characterized by different SMA bloodstream. Small for gestational age (SGA) might be a confounding factor affecting intestinal bloodflow. And infants with delayed initiation or slow advancement of feeding exhibited characteristic intestinal perfusion.ConclusionsIn VLBWI, early SMA ultrasound shows the potential to predict NEC. It is reasonable to speculate that SMA bloodstream is related to intestinal structural and functional integrity

catena-Poly[[(2,2′-bipyridine)­manganese(II)]-μ3-4,4′-sulfonyl­dibenzoato]

In the title compound, [Mn(C14H8O6S)(C10H8N2)]n, the MnII ion is coordinated by four O atoms from three 4,4′-sulfonyl­dibenzoate (sdba) ligands and two N atoms from one 2,2′-bipyridine (2,2′-bipy) ligand in a distorted octa­hedral geometry. The manganese atoms are alternately bridged either by two sdba ligands, with an Mn⋯Mn separation of 12.284 (1) Å, or by two carboxyl­ate groups from two sdba ligands, with an Mn⋯Mn separation of 4.064 (1) Å, thus producing polymeric chains propagated in [101]. Weak inter­molecular C—H⋯O hydrogen bonds and π–π inter­actions [centroid–centroid distance of 3.730 (3) Å between the aromatic rings of neighbouring polymeric chains] further stabilize the crystal packing

4-(3-Carb­oxy-1-ethyl-6-fluoro-4-oxo-1,4-dihydroquinolin-7-yl)piperazin-1-ium 4-carb­oxy­benzoate–benzene-1,4-dicarb­oxy­lic acid (2/1)

In the title compound, C16H19FN3O3 +·C8H5O4 −·0.5C8H6O4, the benzene-1,4-dicarb­oxy­lic acid mol­ecule is located on a centre of symmetry. In the crystal, the mol­ecules and ions are connected by inter­molecular C—H⋯O and O—H⋯O hydrogen bonds and π–π stacking inter­actions [with a centroid–centroid distance of 3.402 (2) Å], generating a three-dimensional supra­molecular structure

Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning

Artificial intelligence (AI) has brought tremendous impacts on biomedical sciences from academic researches to clinical applications, such as in biomarkers' detection and diagnosis, optimization of treatment, and identification of new therapeutic targets in drug discovery. However, the contemporary AI technologies, particularly deep machine learning (ML), severely suffer from non-interpretability, which might uncontrollably lead to incorrect predictions. Interpretability is particularly crucial to ML for clinical diagnosis as the consumers must gain necessary sense of security and trust from firm grounds or convincing interpretations. In this work, we propose a tensor-network (TN)-ML method to reliably predict lung cancer patients and their stages via screening Raman spectra data of Volatile organic compounds (VOCs) in exhaled breath, which are generally suitable as biomarkers and are considered to be an ideal way for non-invasive lung cancer screening. The prediction of TN-ML is based on the mutual distances of the breath samples mapped to the quantum Hilbert space. Thanks to the quantum probabilistic interpretation, the certainty of the predictions can be quantitatively characterized. The accuracy of the samples with high certainty is almost 100$\%$. The incorrectly-classified samples exhibit obviously lower certainty, and thus can be decipherably identified as anomalies, which will be handled by human experts to guarantee high reliability. Our work sheds light on shifting the ``AI for biomedical sciences'' from the conventional non-interpretable ML schemes to the interpretable human-ML interactive approaches, for the purpose of high accuracy and reliability.Comment: 10 pages, 7 figure

Bis(2-carboxybenzo­ato-κO 1)bis­[1-cyclo­propyl-6-fluoro-4-oxo-7-(piperazin-4-ium-1-yl)-1,4-dihydro­quinoline-3-carboxyl­ato-κ2 O 3,O 4]manganese(II) dihydrate

The title compound, [Mn(C17H18FN3O3)2(C8H5O4)2]·2H2O or [Mn(cfH)2(1,2-Hbdc)2]·2H2O (cfH = ciprofloxacin = 1-cyclo­propyl-6-fluoro-1,4-dihydro-4-oxo-7-(1-piperazin­yl)-3-quinoline carb­oxy­lic acid, 1,2-bdc = benzene-1,2-dicarboxyl­ate), has been prepared under hydro­thermal conditions. The Mn2+ atom, located on an inversion centre, exhibits a distorted octa­hedral geometry, coordinated by four O atoms from two symmetry-related zwitterionic ciprofloxacin ligands in the equatorial positions and two O atoms of two 1,2-Hbdc ligands in the axial positions. The complex mol­ecules are linked into a two-dimensional network through N—H⋯O and OW—H⋯O hydrogen bonds. A strong intramolecular hydrogen bond between the carboxyl/carboxylate groups of the 1,2-Hbdc anion is also present. The layers are further extended through off-set aromatic π–π stacking inter­actions of cfH groups [centroid–centroid distance of 3.657 (2) Å] into the final three-dimensional supra­molecular arrays

Host factors do not influence the colonization or infection by fluconazole resistant Candida species in hospitalized patients

Nosocomial yeast infections have significantly increased during the past two decades in industrialized countries, including Taiwan. This has been associated with the emergence of resistance to fluconazole and other antifungal drugs. The medical records of 88 patients, colonized or infected with Candida species, from nine of the 22 hospitals that provided clinical isolates to the Taiwan Surveillance of Antimicrobial Resistance of Yeasts (TSARY) program in 1999 were reviewed. A total of 35 patients contributed fluconazole resistant strains [minimum inhibitory concentrations (MICs) ≧ 64 mg/l], while the remaining 53 patients contributed susceptible ones (MICs ≦ 8 mg/l). Fluconazole resistance was more frequent among isolates of Candida tropicalis (46.5%) than either C. albicans (36.8%) or C. glabrata (30.8%). There was no significant difference in demographic characteristics or underlying diseases among patients contributing strains different in drug susceptibility