Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion.

Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.

Profile analysis of differentially expressed long non­coding RNAs in metabolic memory induced by high glucose in human umbilical vein endothelial cells.

Numerous long non-coding RNAs (lncRNAs) are dysregulated in the hyperglycemia-induced phenomenon of metabolic memory (MM). In the present study, the significance of these lncRNAs in MM was explored by screening for MM-involved differentially expressed lncRNAs (MMDELs) in human umbilical vein endothelial cells (HUVECs) induced by high glucose. A total of nine HUVEC samples were divided into three groups to mimic conditions of low and high glucose environments, as well as induce the state of metabolic memory. The expression of lncRNAs was profiled using RNA sequencing. Bioinformatic analysis was performed using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases to explore the parental genes from which the lncRNAs are transcribed and target genes of the MMDELs and generate enrichment datasets. Reverse transcription-quantitative PCR was performed to validate the expression levels of the selected lncRNAs. The present study identified 308 upregulated and 157 downregulated MMDELs, which were enriched in numerous physiologic processes. Key functional enrichment terms included 'cell cycle', 'oocyte meiosis' and 'p53 signaling pathway'. In conclusion, certain MMDELs may regulate the expression level of highly associated mRNAs through various mechanisms and pathways, thereby interfering with several processes, such as the regulation of the cell cycle, and affecting vascular endothelial cell function. Furthermore, the disorders of these lncRNAs can be retained in MM, further investigation into the functions of these lncRNAs may result in novel insights and treatments, which could help control MM in patients with diabetes.

Mechanochemical-Assisted Extraction and Hepatoprotective Activity Research of Flavonoids from Sea Buckthorn (Hippophaë rhamnoides L.) Pomaces.

Pomaces of sea buckthorn berry were usually side-products during the processing of juice. Due to a lack of an economical and effective extraction method, it was typically recognized as waste. For the purpose of resource utilization, the mechanochemical-assisted extraction (MCAE) method was applied to develop an ecofriendly extraction method and product with better pharmacology activity. The parameters were investigated through response surface methodology (RSM) design experiments. The processing conditions were optimized as follows: amount of Na2CO3 40%, ball-to-material rate 29:1 g/g, milling speed 410 rpm, milling time 24 min, extraction temperature 25 °C, extraction time 20 min and the solid-to-solution ratio 1:10 g/mL. Under these conditions, the yields of flavonoids from sea buckthorn pomaces were 26.82 ± 0.53 mg/g, which corresponds to an increase of 2 times in comparison with that extracted by the heat reflux extraction method. Meanwhile, the hepatoprotective activity of sea buckthorn pomaces extracts was studied by the liver injury induced by ip injection of tetracycline. Biochemical and histopathological studies showed that biomarkers in serum and liver of nonalcoholic fatty liver disease (NAFLD) mice were significantly ameliorated when sea buckthorn flavonoids extracted by MCAE were used. Altogether, these results demonstrate that, as a green and efficient extraction, MCAE treatment could increase the extraction yield of sea buckthorn flavonoids, meanwhile it could exhibit significant activity of improving liver function. This research provided a new way to use pomaces of sea buckthorn as a functional food. It also has great value on the comprehensive utilization of nature's resources.

Copper nitrate-catalyzed oxidative coupling of unactivated C(sp3)-H bonds of ethers and alkanes with N-hydroxyphthalimide: synthesis of N-hydroxyimide esters.

A copper nitrate-catalyzed cross-dehydrogenative coupling reaction between N-hydroxyphthalimide (NHPI) and ethers/alkanes has been described. The reaction is accomplished smoothly by using simple and green molecular oxygen as the oxidant, providing an alternative for the efficient synthesis of N-alkoxyphthalimides. In addition, it was found that when tert-butyl ethers were used as substrates, unexpected N-hydroxyimide ester derivatives were obtained in moderate to excellent yields. To further understand this unusual transformation, control experiments were performed and a plausible mechanism was proposed.

Immobilization of bovine serum albumin-protected gold nanoclusters by using polyelectrolytes of opposite charges for the development of the reusable fluorescent Cu2+-sensor.

In this paper, we reported a facile method of fabricating a reusable fluorescent Cu(2+)-sensor. To fabricate the reusable sensor, the bovine serum albumin-protected gold nanoclusters (BSAGNCs) were complexed with polyelectrolytes, i.e., positively charged polydiallyldimethylammonium (PDDA) and negatively charged polystyrenesulfonate (PSS), and were coated on a glass slide. The prepared film-modified glass slides exhibited the recyclability of fluorescent signal "off-on" behaviors: the fluorescence could be switched "off" by immersing the film sensors in Cu(2+) solution and "on" by washing with ethylene diamine tetraacetic acid (EDTA) solution. The prepared film-modified glass slides exhibited high selectivity towards Cu(2+) the fluorescence quenching behavior in the form of the Stern-Volmer equation. In addition, the spiked tap water samples were analyzed with satisfactory results. These demonstrations provide a new convenient approach to develop the BSAGNCs-based, reusable fluorescence sensors.