Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records.

PURPOSE: Predictively diagnosing infectious diseases helps in providing better treatment and enhances the prevention and control of such diseases. This study uses actual data from a hospital. A multiple infectious disease diagnostic model (MIDDM) is designed for conducting multi-classification of infectious diseases so as to assist in clinical infectious-disease decision-making. METHODS: Based on actual hospital medical records of infectious diseases from December 2012 to December 2020, a deep learning model for multi-classification research on infectious diseases is constructed. The data includes 20,620 cases covering seven types of infectious diseases, including outpatients and inpatients, of which training data accounted for 80%, i.e., 16,496 cases, and test data accounted for 20%, i.e., 4124 cases. Through the auto-encoder, data normalization and sparse data densification processing are carried out to improve the model training effect. A residual network and attention mechanism are introduced into the MIDDM model to improve the performance of the model. RESULT: MIDDM achieved improved prediction results in diagnosing seven kinds of infectious diseases. In the case of similar disease diagnosis characteristics and similar interference factors, the prediction accuracy of disease classification with more sample data is significantly higher than the prediction accuracy of disease classification with fewer sample data. For instance, the training data for viral hepatitis, influenza, and hand foot and mouth disease were 2954, 3924, and 3015 respectively and the corresponding test accuracy rates were 99.86%, 98.47%, and 97.31%. There is less training data for syphilis, infectious diarrhea, and measles, i.e., 1208, 575, and 190 respectively and the corresponding test accuracy rates were noticeably lower, i.e., 83.03%, 87.30%, and42.11%. We also compared the MIDDM model with the models used in other studies. Using the same input data, taking viral hepatitis as an example, the accuracy of MIDDM is 99.44%, which is significantly higher than that of XGBoost (96.19%), Decision tree (90.13%), Bayesian method (85.19%), and logistic regression (91.26%). Other diseases were also significantly better predicted by MIDDM than by these three models. CONCLUSION: The application of the MIDDM model to multi-class diagnosis and prediction of infectious diseases can improve the accuracy of infectious-disease diagnosis. However, these results need to be further confirmed via clinical randomized controlled trials.

Intelligent virtual case learning system based on real medical records and natural language processing.

BACKGROUND: Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are actively conducting research and exploration in this area. In particular, given the shortage of human resources, the need to maintain social distancing to prevent the spread of the epidemics, and the increase in the cost of medical education, it is critical to harness online learning to promote medical education. A virtual case learning system that uses natural language processing technology to process and present a hospital's real medical records and evaluate student responses can effectively improve medical students' clinical thinking abilities. OBJECTIVE: The purpose of this study is to develop a virtual case system, AIteach, based on actual complete hospital medical records and natural language processing technology, and achieve clinical thinking ability improvement through a contactless, self-service, trial-and-error system application. METHODS: Case extraction is performed on a hospital's case data center and the best-matching cases are produced through natural language processing, word segmentation, synonym conversion, and sorting. A standard clinical questioning data module, virtual case data module, and student learning difficulty module are established to achieve simulation. Students can view the objective examination and inspection data of actual cases, including details of the consultation and physical examination, and automatically provide their learning response via a multi-dimensional evaluation system. In order to assess the changes in students' clinical thinking after using AIteach, 15 medical graduate students were subjected to two simulation tests before and after learning through the virtual case system. The tests, which included the full-process case examination of cases having the same difficulty level, examined core clinical thinking test points such as consultation, physical examination, and disposal, and generated multi-dimensional evaluation indicators (rigor, logic, system, agility, and knowledge expansion). Thus, a complete and credible evaluation system is developed. RESULTS: The AIteach system used an internal and external double-cycle learning model. Students collect case information through online inquiries, physical examinations, and other means, analyze the information for feedback verification, and generate their detailed multi-dimensional clinical thinking after learning. The feedback report can be evaluated and its knowledge gaps analyzed. Such learning based on real cases is in line with traditional methods of disease diagnosis and treatment, and addresses the practical difficulties in reflecting actual disease progression while keeping pace with recent research. Test results regarding short-term learning showed that the average score (P < 0.01) increased from 69.87 to 85.6, the five indicators of clinical thinking evaluation improved, and there was obvious logical improvement, reaching 47%. CONCLUSION: By combining real cases and natural language processing technology, AIteach can provide medical students (including undergraduates and postgraduates) with an online learning tool for clinical thinking training. Virtual case learning helps students to cultivate clinical thinking abilities even in the absence of clinical tutor, such as during pandemics or natural disasters.

STAT3 Promotes Schistosome-Induced Liver Injury by Inflammation, Oxidative Stress, Proliferation, and Apoptosis Signal Pathway.

Schistosomiasis is a parasitic helminth disease that can cause organ lesions leading to health damage. During a schistosome infection, schistosome eggs can flow into the liver along the portal vein. Numerous inflammatory cells gather around the eggs, causing granulomas and fibrosis in the liver. In this process, many molecules are involved in the initiation and regulation of the fibrous scar formation. However, the precise molecular mechanisms responsible for the progression of granuloma formation and fibrosis initiation caused by schistosome infection have not been extensively studied. In this study, C57BL/6 wild-type mice and Stat3flox/flox Alb-Cre mice were infected with cercariae of Schistosoma japonicum Liver injury, effector molecule levels, and RNA transcriptome resequencing of liver tissue were detected at 4, 5, and 6 weeks postinfection. We investigated the role of STAT3 (signal transducer and activator of transcription 3) in Schistosoma-induced liver injury in mice. After 6 weeks postinfection, there was obvious liver fibrosis. A sustained pathological process (inflammation, oxidative stress, proliferation, and apoptosis) occurred in S. japonicum-induced liver fibrosis initiation. Meanwhile, we observed activation of the STAT3 pathway in hepatic injury during S. japonicum infection by RNA transcriptome resequencing. Liver deficiency of phospho-STAT3 alleviated infection-induced liver dysfunction, hepatic granuloma formation, and fibrosis initiation. It also promoted STAT3-dependent apoptosis and reduced liver inflammation, oxidative stress, and proliferation. Our results suggest that STAT3 signal pathway and its mediating inflammation, oxidative stress, proliferation, and apoptosis are involved in S. japonicum-induced liver injury and may be a new potential guideline for the treatment of schistosomiasis.

Intermedin alleviates pathological cardiac remodeling by upregulating klotho.

Cardiac remodeling is accompanied by cardiac hypertrophy, fibrosis, dysfunction, and eventually leading to heart failure. Intermedin (IMD), as a paracrine/autocrine peptide, has a protective effect in cardiovascular diseases. In this study, we elucidated the role and the underlying mechanism of IMD in pathological remodeling. Pathological remodeling mouse models were induced by abdominal aorta constriction for 4 weeks or angiotensin II (Ang II) infusion for 2 weeks in wildtype, IMD-overexpression, IMD-knockout and klotho-knockdown mice. Western blot, real-time PCR, histological staining, echocardiography and hemodynamics were used to detect the role of IMD in cardiac remodeling. Cardiac hypertrophy, fibrosis and dysfunction were significantly aggravated in IMD-knockout mice versus wildtype mice, and the expression of klotho was downregulated. Conversely, cardiac remodeling was alleviated in IMD-overexpression mice, and the expression of klotho was upregulated. Hypertension induced by Ang II infusion rather than abdominal aorta constriction was mitigated by IMD. However, the cardioprotective effect of IMD was blocked in klotho-knockdown mice. Similar results were found in cultured neonatal rat cardiomyocytes, which was pretreated with IMD before Ang II stimulation. Mechanistically, IMD inhibited the phosphorylation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and the activity of calcineurin to protect against cardiac hypertrophy through upregulating klotho in vivo and in vitro. Furthermore, peroxisome proliferator-activated receptor γ (PPARγ) might mediate IMD upregulating klotho. In conclusion, pathological remodeling may be alleviated by endogenous IMD, which inhibits the expression of calcineurin and p-CaMKII by upregulating klotho via the PPARγ pathway. It suggested that IMD might be a therapeutic target for heart disease.

Observations of Bacterial Biofilm on Ureteral Stent and Studies on the Distribution of Pathogenic Bacteria and Drug Resistance.

OBJECTIVE: This study aims to observe the morphological characteristics of bacterial biofilm on the surface of ureteral stents and analyze distribution characteristics of pathogens on the bacterial biofilm and drug resistance. METHODS: Ureteral stents were sampled from 129 patients. A scanning electron microscope was used to observe the morphological characteristics of bacterial biofilms, and the Congo red medium was applied to screen bacterial biofilm strains on the renal pelvis section, ureter section, and bladder section respectively. Urine culture was performed, and the drug sensitive test analysis was carried out for the pathogenic bacteria detected. RESULTS: Bacterial biofilms can be observed on the surface of ureteral stents, and these bacteria are embraced by large amounts of fiber membranes. A total of 107 patients were found to be positive for biofilms with a positive rate of 82.9%. The positive rates of the bladder section, ureter section, renal pelvis section, and urine culture were 85.0, 42.9, 67.3, and 24.3% respectively. Pathogenic bacteria mainly concentrated on Escherichia coli, and the drug resistance rate of the bacterial biofilm strains on the ureteral stent was relatively higher. CONCLUSION: The bacterial biofilm on the ureteral stent is an important factor that induces catheter-associated urinary tract infections.

Endoplasmic reticulum stress-mediated apoptosis is activated in intestines of mice with Trichinella spiralis infection.

Gastrointestinal helminth infection, including Trichinella spiralis, initiates a series of intestinal structural, cellular and physiological changes. Intestinal invasion is an important stage of trichinellosis because it determines the development and subsequent course of the disease and its consequences. Apoptosis mediated by endoplasmic reticulum stress (ERS) plays a key role in infectious diseases, but the effect of T. spiralis infection on inducing apoptosis in the small intestine has been neglected. We investigated apoptosis and changes in ERS-associated apoptosis molecules in the intestine of mice with T. spiralis infection. TUNEL staining and detection of the apoptotic marker cleaved caspase 3 revealed that apoptosis occurred in the mouse intestine at days 3 and 7 post-infection. The ER chaperone 78-kDa glucose-regulated protein (GRP78) was upregulated at days 3 and 7 post-infection. The ERS-associated apoptosis molecules C/EBP homologous protein, cleaved caspase 12 and c-Jun NH2-terminal kinase were upregulated at days 3 and 7, days 3, 7 and 10 and days 7 and 10 post-infection, respectively. Thus, apoptosis occurred in the intestine of mice with T. spiralis infection, and the ERS-mediated apoptosis pathway was activated by infection with this small intestine dwelling nematode.

An orexin-receptor-2-mediated heart-brain axis in cardiac pain.

Orexin is a neuropeptide released from hypothalamus regulating feeding, sleeping, arousal, and cardiovascular activity. Past research has demonstrated that orexin receptor 2 (OX2R) agonist infusion in the brain results in sympathoexcitatory responses. Here, we found that epicardial administration of OX2R agonism leads to opposite responses. We proved that OX2R is expressed mainly in DRG neurons and transported to sensory nerve endings innervating the heart. In a capsaicin-induced cardiac sympathetic afferent reflex (CSAR) model, we recorded the calcium influx in DRG neurons, measured heart rate variability, and examined the PVN c-Fos activity to prove that epicardial OX2R agonism administration could attenuate capsaicin-induced CSAR. We further showed that OX2R agonism could partially rescue acute myocardial infarction by reducing sympathetic overactivation. Our data indicate that epicardial application of OX2R agonist exerts a cardioprotective effect by attenuating CSAR. This OX2R-mediated heart-brain axis may provide therapeutic targets for acute cardiovascular diseases.

Identification and characterization of lysine-rich proteins and starch biosynthesis genes in the opaque2 mutant by transcriptional and proteomic analysis.

BACKGROUND: The opaque2 mutant is valuable for producing maize varieties with enhanced nutritional value. However, the exact mechanisms by which it improves protein quality and creates a soft endosperm texture are unclear. Given the importance of improving nutritional quality in grain crops, a better understanding of the physiological basis for these traits is necessary. RESULTS: In this study, we combined transcript profiling and proteomic analysis to better understand which genes and proteins are altered by opaque2 in the W64A inbred line. These analyses showed that the accumulation of some lysine-rich proteins, such as sorbitol dehydrogenase and glyceraldehyde3-phosphate dehydrogenase, was increased in mature kernels and may contribute substantially to the lysine content of opaque2 endosperm. Some defense proteins such as beta-glucosidase aggregating factor were strongly down regulated and may be regulated directly by opaque2. The mutant also had altered expression of a number of starch biosynthesis genes and this was associated with a more highly crystalline starch. CONCLUSIONS: The results of these studies revealed specific target genes that can be investigated to further improve nutritional quality and agronomic performance of high lysine maize lines, particularly those based on the presence of the opaque2 mutation. Alteration of amylopectin branching patterns in opaque2 starch could contribute to generation of the soft, starchy endosperm.

Systemic cytokine profiles and splenic toll-like receptor expression during Trichinella spiralis infection.

Parasitic helminth and their products can suppress or modulate the host immune response for long-term survival and continued infection. Commonly, helminth can induce conditional T helper cell type 2 (Th2) response, regulatory T cell and cytokines, and altered function of antigen presentation cells by modulating toll-like receptors (TLRs). The helminth Trichinella spiralis establishes chronic infection in skeletal muscles of a wide range of mammalian hosts. We infected mice with T. spiralis and investigated Th1/Th2/Th17 cytokine profiles in serum and expression of TLRs and related signal molecules in spleen at various times post-infection. The infection evoked a mixed Th1/Th2 and inhibited Th17 immune response, with initial predominance of a Th1 response in intestine stage and subsequent predominance of a Th2 response in muscle stage. Different stages of infection had different impacts on the expression of TLRs and related signaling molecules. In the adult stage of infection, TLR1 and TLR4 were upregulated and the MyD88-dependent signal pathway was activated. The muscle larvae inhibited TLR4 and TRIF-dependent signal pathway. Our results implied that T. spiralis infection may regulate Th1/Th2/Th17 cytokine production through TLRs.

Construction and effectiveness evaluation of a knowledge-based infectious disease monitoring and decision support system.

To improve the hospital's ability to proactively detect infectious diseases, a knowledge-based infectious disease monitoring and decision support system was established based on real medical records and knowledge rules. The effectiveness of the system was evaluated using interrupted time series analysis. In the system, a monitoring and alert rule library for infectious diseases was generated by combining infectious disease diagnosis guidelines with literature and a real medical record knowledge map. The system was integrated with the electronic medical record system, and doctors were provided with various types of real-time warning prompts when writing medical records. The effectiveness of the system's alerts was analyzed from the perspectives of false positive rates, rule accuracy, alert effectiveness, and missed case rates using interrupted time series analysis. Over a period of 12 months, the system analyzed 4,497,091 medical records, triggering a total of 12,027 monitoring alerts. Of these, 98.43% were clinically effective, while 1.56% were invalid alerts, mainly owing to the relatively rough rules generated by the guidelines leading to several false alarms. In addition, the effectiveness of the system's alerts, distribution of diagnosis times, and reporting efficiency of doctors were analyzed. 89.26% of infectious disease cases could be confirmed and reported by doctors within 5 min of receiving the alert, and 77.6% of doctors could complete the filling of 33 items of information within 2 min, which is a reduction in time compared to the past. The timely reminders from the system reduced the rate of missed cases by doctors; the analysis using interrupted time series method showed an average reduction of 4.4037% in the missed-case rate. This study proposed a knowledge-based infectious disease decision support system based on real medical records and knowledge rules, and its effectiveness was verified. The system improved the management of infectious diseases, increased the reliability of decision-making, and reduced the rate of underreporting.

Method and application of information sharing throughout the emergency rescue process based on 5G and AR wearable devices.

The 2022 Winter Olympics were held in the three competition zones of Beijing, Yanqing and Zhangjiakou, China. The venues of this Winter Olympics were scattered and the terrain was complex. Moreover, the medical resources of Hebei and Beijing were relatively unbalanced. In the medical security of major events, the connection between first aid and in-hospital processes is of the utmost importance to rescue quality. 5th generation mobile network (5G) applications in medical scenarios are on the rise. It would be of great relevance to fully use 5G's low-latency and high-speed features to share the process information of patients, ambulance personnel, and the destination hospital's rescue team at emergency scenes and in transportation, improving rescue efficiency. This paper proposes a system scheme of cross-institutional emergency health information sharing based on 5G and augmented reality wearable devices. It also integrates the construction method of monitoring and other sign data sharing, in addition to testing the proposed scheme's service quality in 5G environments. In the deployment area of the 5G emergency medical rescue information sharing scheme for the Beijing Winter Olympic Games, we selected two designated medical support institutions for testing. The test adopted a combination of fixed-point and driving tests to experiment on the service data, voice service, and streaming media indicators. The 5G signal's coverage rate was close to 100%, the standalone connection's success rate was 100%, and the drop rate was 0. The average downlink rate of multiple scenarios was 620mbps, and the average uplink rate of 5G was over 71.8mbps, which is higher than the average 5G level in China. The downlink rate was more than 20 times larger than the 4th generation mobile network (4G) rate. This study's proposed scheme demonstrates the importance of 5G applications in emergency response and support, in addition to providing a suitable scheme for the integration of 5G networks in the medical scene.

Microstructure and Biomechanical Properties in Selective Laser Melting of Porous Metal Implants.

Two kinds of porous structure design strategies, ring-support (RS) and column-support (CS), are proposed for human implants. The accurate design of porosity is realized by adjusting the pore characteristics, such as strut diameter, pore diameter, and unit size. Porous specimens with porosity of 50%, 60%, 70%, and 80% were prepared by selective laser melting. The three-dimensional pore structure is basically consistent with the design characteristics, and the measured porosity is slightly lower than design value. The microstructure, microhardness, and friction and wear properties of the samples were studied. The results show that the performance along the scanning orientation is slightly better than that along the forming orientation. The compression and dynamic elastic modulus of porous specimens with different structures and porosities were analyzed. The CS porous with 60-80% porosity has suitable compressive strength and elastic modulus, which is close to that of human tissue, and effectively avoids the stress shielding phenomenon.

Intermedin alleviates diabetic vascular calcification by inhibiting GLUT1 through activation of the cAMP/PKA signaling pathway.

BACKGROUND AND AIMS: Vascular calcification (VC) is regarded as an independent risk factor for cardiovascular events in type 2 diabetic patients. Glucose transporter 1 (GLUT1) involves VC. Intermedin/Adrenomedullin-2 (IMD/ADM2) is a cardiovascular protective peptide that can inhibit multiple disease-associated VC. However, the role and mechanism of IMD in diabetic VC remain unclear. Here, we investigated whether IMD inhibits diabetic VC by inhibiting GLUT1. METHODS AND RESULTS: It was found that plasma IMD concentration was significantly decreased in type 2 diabetic patients and in fructose-induced diabetic rats compared with that in controls. Plasma IMD content was inversely correlated with fasting blood glucose level and VC severity. IMD alleviated VC in fructose-induced diabetic rats. Deficiency of Adm2 aggravated and Adm2 overexpression attenuated VC in high-fat diet-induced diabetic mice. In vitro, IMD mitigated high glucose-induced calcification of vascular smooth muscle cells (VSMCs). Mechanistically, IMD reduced advanced glycation end products (AGEs) content and the level of receptor for AGEs (RAGE). IMD decreased glucose transporter 1 (GLUT1) levels. The inhibitory effect of IMD on RAGE protein level was blocked by GLUT1 knockdown. GLUT1 knockdown abolished the effect of IMD on alleviating VSMC calcification. IMD receptor antagonist IMD17-47 and cyclic adenosine monophosphate/protein kinase A (cAMP/PKA) inhibitor H89 abolished the inhibitory effects of IMD on GLUT1 and VSMC calcification. CONCLUSIONS: These findings revealed that IMD exerted its anti-calcification effect by inhibiting GLUT1, providing a novel therapeutic target for diabetic VC.

A SARS-CoV-2-specific CAR-T-cell model identifies felodipine, fasudil, imatinib, and caspofungin as potential treatments for lethal COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm is closely associated with coronavirus disease 2019 (COVID-19) severity and lethality. However, drugs that are effective against inflammation to treat lethal COVID-19 are still urgently needed. Here, we constructed a SARS-CoV-2 spike protein-specific CAR, and human T cells infected with this CAR (SARS-CoV-2-S CAR-T) and stimulated with spike protein mimicked the T-cell responses seen in COVID-19 patients, causing cytokine storm and displaying a distinct memory, exhausted, and regulatory T-cell phenotype. THP1 remarkably augmented cytokine release in SARS-CoV-2-S CAR-T cells when they were in coculture. Based on this "two-cell" (CAR-T and THP1 cells) model, we screened an FDA-approved drug library and found that felodipine, fasudil, imatinib, and caspofungin were effective in suppressing the release of cytokines, which was likely due to their ability to suppress the NF-κB pathway in vitro. Felodipine, fasudil, imatinib, and caspofungin were further demonstrated, although to different extents, to attenuate lethal inflammation, ameliorate severe pneumonia, and prevent mortality in a SARS-CoV-2-infected Syrian hamster model, which were also linked to their suppressive role in inflammation. In summary, we established a SARS-CoV-2-specific CAR-T-cell model that can be utilized as a tool for anti-inflammatory drug screening in a fast and high-throughput manner. The drugs identified herein have great potential for early treatment to prevent COVID-19 patients from cytokine storm-induced lethality in the clinic because they are safe, inexpensive, and easily accessible for immediate use in most countries.

Polycyclic aromatic hydrocarbons and organochlorine pesticides in fish from Taihu Lake: their levels, sources, and biomagnification.

The investigation of biomagnification of polycyclic aromatic hydrocarbons (PAHs) and endosulfan, an organochlorine pesticide (OCP) and a new persistent organic pollutant, has been limited in freshwater food chains. The objective of the present study was to investigate the levels with focus on the sources and biomagnification of PAHs and OCPs in fish from Taihu Lake, China. In 193 samples of 24 species investigated, the concentrations ranged from 289 to 9 500 ng/g lipid weight (lw) for PAHs, and from 121 to 904 ng/g lw for OCPs, indicating that the fish in the lake was moderately contaminated. The PAHs mainly originated from both unburned petroleum and combustion of fossil fuels, and the OCPs from aged residues. It was unlikely that most of the PAHs and OCPs were biodiluted through the food chain because their trophic magnification factors were higher than one nevertheless the P-values >0.05. Aldrin, dieldrin, p,p'-DDE, p,p'-DDD, and endosulfan sulfate were significantly biomagnified through the food chain.

Levels and distribution of synthetic musks and polycyclic aromatic hydrocarbons in sludge collected from Guangdong Province.

The levels and distribution of six polycyclic musks, three nitromusks and 15 polycyclic aromatic hydrocarbons (PAHs) were investigated in sludge collected from 19 municipal wastewater treatment plants (WWTPs) in six cities in Guangdong Province, China. PAHs were detected in all of the sludge samples, and the levels of the total 15 PAHs ranged from 177.2-4421.8 µg/kg dry weight (dw). Four polycyclic musks, 4-acetyl-1,1-dimethyl-6-tert-butylindan (ADBI), 6-acetyl-1,1,2,3,3,5-hexamethylindan (AHMI), 1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethylcyclopenta (g) -2-benzopyran (HHCB) and 7-acetyl -1,1,3,4,4,6-hexamethyl-1,2,3,4-tetrahydro naphthalene (AHTN), were found in these samples. The total concentrations of polycyclic musks varied from 794.4-12960.3 µg/kg dw, with HHCB and AHTN being the main components. Of the three nitromusks, 2,6-dinitro-3-methoxy-4-tert- butyl - toluene (MA) was only found in one sludge sample at the limit of detection (LOD) level, while 1-tert-butyl-3,5-dimethyl-2,4,6-trinitrobenzene (Musk xylene, MX) and 4-acetyl-1-tert-butyl-3,5-dimethyl-2,6-dinitrobenzene (Musk ketone, MK) were found at levels ranging from the LOD to 65.8 µg/kg dw and LOD to 172.7 µg/kg dw, respectively, in most of the sludge samples. The PAHs, polycyclic musks and nitro musks were also shown to have various distribution patterns, possibly due to their different wastewater sources and wastewater treatment technology.

SARS-CoV-2 Survival in Common Non-Alcoholic and Alcoholic Beverages.

SARS-CoV-2, the causative agent of COVID-19, is known to be transmitted by respiratory droplets and aerosols. Since the virus is shed at high concentrations in respiratory secretions and saliva, SARS-CoV-2 would also be expected to be transmitted through activities that involve the transfer of saliva from one individual to another, such as kissing or sharing beverages. To assess the survival of infectious SARS-CoV-2 in common beverages, we quantified infectious virus by plaque assays one hour after inoculation into 18 non-alcoholic and 16 alcoholic beverages, plus saliva, and also 7 days later for 5 of these beverages. SARS-CoV-2 remains infectious with minimal reductions in several common beverages, including milk and beer. However, cocoa, coffee, tea, fruit juices, and wine contain antiviral compounds that inactivate SARS-CoV-2. Although hard liquors containing 40% alcohol immediately inactivate SARS-CoV-2, mixing with non-alcoholic beverages reduces the antiviral effects. In summary, SARS-CoV-2 can be recovered from commonly consumed beverages in a beverage type and time-dependent manner. Although aerosol or droplet transmission remains the most likely mode of transmission, our findings combined with others suggest that beverages contaminated with SARS-CoV-2 during handling, serving, or through sharing of drinks should be considered as a potential vehicle for virus transmission.

Orexin receptor type 2 agonism inhibits thermogenesis in brown adipose tissue by attenuating afferent innervation.

Orexin signaling has been associated with energy expenditure and brown adipose tissue (BAT) function. However, conflicting data exist in the field about how orexin signaling regulates BAT thermogenesis. In this study, we show that a specific orexin receptor type 2 (OX2R) agonist [Ala11, D-Leu15]-OxB (OB-Ala) inhibited intrascapular brown adipose tissue (iBAT) thermogenesis by reducing sympathetic output to iBAT. This effect is mediated by OX2Rs located on afferent nerve endings innervating iBAT instead of brown adipocyte itself. Microinjection of OB-Ala into iBAT inhibited iBAT thermogenesis in mice upon cold exposure and neuronal activity in the paraventricular nucleus. Findings suggest that OB-Ala could inhibit iBAT thermogenesis by attenuating sensory input thereby inhibiting the sympathetic-sensory iBAT feedback loop. Our study uncovers a novel primary action site of orexin in the regulation of energy balance.

SARS-CoV-2 Remains Infectious on Refrigerated Deli Food, Meats, and Fresh Produce for up to 21 Days.

SARS-CoV-2, the virus that causes COVID-19, has been detected on foods and food packaging and the virus can infect oral cavity and intestinal cells, suggesting that infection could potentially occur following ingestion of virus-contaminated foods. To determine the relative risk of infection from different types of foods, we assessed survival of SARS-CoV-2 on refrigerated ready-to-eat deli items, fresh produce, and meats (including seafood). Deli items and meats with high protein, fat, and moisture maintained infectivity of SARS-CoV-2 for up to 21 days. However, processed meat, such as salami, and some fresh produce exhibited antiviral effects. SARS-CoV-2 also remained infectious in ground beef cooked rare or medium, but not well-done. Although infectious SARS-CoV-2 was inactivated on the foods over time, viral RNA was not degraded in similar trends, regardless of food type; thus, PCR-based assays for detection of pathogens on foods only indicate the presence of viral RNA, but do not correlate with presence or quantity of infectious virus. The survival and high recovery of SARS-CoV-2 on certain foods support the possibility that food contaminated with SARS-CoV-2 could potentially be a source of infection, highlighting the importance of proper food handling and cooking to inactivate any contaminating virus prior to consumption.

Maximum Likelihood Reconstruction of Water Cherenkov Events With Deep Generative Neural Networks.

Large water Cherenkov detectors have shaped our current knowledge of neutrino physics and nucleon decay, and will continue to do so in the foreseeable future. These highly capable detectors allow for directional and topological, as well as calorimetric information to be extracted from signals on their photosensors. The current state-of-the-art approach to water Cherenkov reconstruction relies on maximum-likelihood estimation, with several simplifying assumptions employed to make the problem tractable. In this paper, we describe neural networks that produce probability density functions for the signals at each photosensor, given a set of inputs that characterizes a particle in the detector. The neural networks we propose allow for likelihood-based approaches to event reconstruction with significantly fewer assumptions compared to traditional methods, and are thus expected to improve on the current performance of water Cherenkov detectors.