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We surveyed nearly all the embedded protostars in seven nearby clouds (Corona Australis, Aquila, Chamaeleon I and II, Ophiuchus North, Ophiuchus, Serpens) with the Atacama Large Millimeter/submillimeter Array at 1.3 mm observations with a resolution of 0.″1. This survey detected 184 protostellar disks, 90 of which were observed at a resolution of 14–18 au, making it one of the most comprehensive high-resolution disk samples across various protostellar evolutionary stages to date. Our key findings include the detection of new annular substructures in two Class I and two flat-spectrum sources, while 21 embedded protostars exhibit distinct asymmetries or substructures in their disks. We find that protostellar disks have a substantially large variability in their radii across all evolutionary classes. In particular, the fraction of large disks with sizes above 60 au decreases as the protostar evolves from Class 0 to Class I. Compiling the literature data, we discovered an increasing trend of the gas disk radii to dust disk radii ratio (R gas,Kep/R mm) with increasing bolometric temperature (T bol). Our results indicate that the dust and gas disk radii decouple during the early Class I stage. However, in the Class 0 stage, the dust and gas disk sizes are similar, which allows for a direct comparison between models and observational data at the earliest stages of protostellar evolution. We show that the distribution of radii in the 52 Class 0 disks in our sample is in high tension with various disk formation models, indicating that protostellar disk formation remains an unsolved question.

We present Atacama Large Millimeter/submillimeter Array observations of the ∼10,000 au environment surrounding 21 protostars in the Orion A molecular cloud tracing outflows. Our sample is composed of Class 0 to flat-spectrum protostars, spanning the full ∼1 Myr lifetime. We derive the angular distribution of outflow momentum and energy profiles and obtain the first two-dimensional instantaneous mass, momentum, and energy ejection rate maps using our new approach: the pixel flux-tracing technique. Our results indicate that by the end of the protostellar phase, outflows will remove ∼2–4 M ⊙ from the surrounding ∼1 M ⊙ low-mass core. These high values indicate that outflows remove a significant amount of gas from their parent cores and continuous core accretion from larger scales is needed to replenish core material for star formation. This poses serious challenges to the concept of cores as well-defined mass reservoirs, and hence to the simplified core-to-star conversion prescriptions. Furthermore, we show that cavity opening angles, and momentum and energy distributions all increase with protostar evolutionary stage. This is clear evidence that even garden-variety protostellar outflows: (a) effectively inject energy and momentum into their environments on 10,000 au scales, and (b) significantly disrupt their natal cores, ejecting a large fraction of the mass that would have otherwise fed the nascent star. Our results support the conclusion that protostellar outflows have a direct impact on how stars get their mass, and that the natal sites of individual low-mass star formation are far more dynamic than commonly accepted theoretical paradigms.

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Without existing protective immunity, an EID may spread rapidly and cause mass casualties in a very short time. Therefore, it is imperative to identify cases with risk of disease progression for the optimized allocation of medical resources in case medical facilities are overwhelmed with a flood of patients. This study has aimed to cope with this challenge from the aspect of preventive medicine by exploiting machine learning technologies. The study has been based on 83,227 hospital admissions with influenza-like illness and we analysed the risk effects of 19 comorbidities along with age and gender for severe illness or mortality risk. The experimental results revealed that the decision rules derived from the machine learning based prediction models can provide valuable guidelines for the healthcare policy makers to develop an effective vaccination strategy. Furthermore, in case the healthcare facilities are overwhelmed by patients with EID, which frequently occurred in the recent COVID-19 pandemic, the frontline physicians can incorporate the proposed prediction models to triage patients suffering minor symptoms without laboratory tests, which may become scarce during an EID disaster. In conclusion, our study has demonstrated an effective approach to exploit machine learning technologies to cope with the challenges faced during the outbreak of an EID.

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x10 3 / μL )], fever (≥38°C), low platelet counts [< 100 (x10 3 / μL )], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96–6.76], 3.17 [95%CI: 2.74–3.66], 3.10 [95%CI: 2.44–3.94], and 1.77 [95%CI: 1.50–2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

Arginine synthesis deficiency due to the suppressed expression of ASS1 (argininosuccinate synthetase 1) represents one of the most frequently occurring metabolic defects of tumor cells. Arginine-deprivation therapy has gained increasing attention in recent years. One challenge of ADI-PEG20 (pegylated ADI) therapy is the development of drug resistance caused by restoration of ASS1 expression and other factors. The goal of this work is to identify novel factors conferring therapy resistance. Multiple, independently derived ADI-resistant clones including derivatives of breast (MDA-MB-231 and BT-549) and prostate (PC3, CWR22Rv1, and DU145) cancer cells were developed. RNA-seq and RT-PCR were used to identify genes upregulated in the resistant clones. Unbiased genome-wide CRISPR/Cas9 knockout screening was used to identify genes whose absence confers sensitivity to these cells. shRNA and CRISPR/Cas9 knockout as well as overexpression approaches were used to validate the functions of the resistant genes both and in xenograft models. The signal pathways were verified by western blotting and cytokine release. Based on unbiased CRISPR/Cas9 knockout screening and RNA-seq analyses of independently derived ADI-resistant (ADIR) clones, aberrant activation of the TREM1/CCL2 axis in addition to ASS1 expression was consistently identified as the resistant factors. Unlike ADIR, MDA-MB-231 overexpressing ASS1 cells achieved only moderate ADI resistance both and , and overexpression of ASS1 alone does not activate the TREM1/CCL2 axis. These data suggested that upregulation of TREM1 is an independent factor in the development of strong resistance, which is accompanied by activation of the AKT/mTOR/STAT3/CCL2 pathway and contributes to cell survival and overcoming the tumor suppressive effects of ASS1 overexpression. Importantly, knockdown of TREM1 or CCL2 significantly sensitized ADIR toward ADI. Similar results were obtained in BT-549 breast cancer cell line as well as castration-resistant prostate cancer cells. The present study sheds light on the detailed mechanisms of resistance to arginine-deprivation therapy and uncovers novel targets to overcome resistance. We uncovered TREM1/CCL2 activation, in addition to restored ASS1 expression, as a key pathway involved in full ADI-resistance in breast and prostate cancer models.

Hypoxia, the reduction of oxygen levels in cells or tissues, elicits a set of genes to adjust physiological and pathological demands during normal development and cancer progression. OCT4, a homeobox transcription factor, is essential for self-renewal of embryonic stem cells, but little is known about the role of OCT4 in non-germ-cell tumorigenesis. Here, we report that hypoxia stimulates a short isoform of OCT4, called OCT4B, via a HIF2α-dependent pathway to induce the epithelial–mesenchymal transition (EMT) and facilitate cancer dissemination. OCT4B overexpression decreased epithelial barrier properties, which led to an increase in cell migration and invasion in lung cancer cells. OCT4B knockdown attenuated HIF2α-induced EMT and inhibited cancer dissemination in cell-line and animal models. We observed that OCT4B bound the SLUG promoter and enhanced its expression, and SLUG silencing inhibited OCT4B-mediated EMT, accompanied with decreased cell migration and invasion. Correlation analysis revealed that OCT4B expression was significantly associated with the SLUG level in lung tumors. These results provide novel insights into OCT4B-mediated oncogenesis in cancer dissemination.

Zika virus (ZIKV) is primarily transmitted by Aedes mosquitoes in the subgenus Stegomyia but can also be transmitted sexually and vertically in humans. STAT1 is an important downstream factor that mediates type I and II interferon signaling. In the current study, we showed that mice with STAT1 knockout (Stat1-/-) were highly susceptible to ZIKV infection. As low as 5 plaque-forming units of ZIKV could cause viremia and death in Stat1-/- mice. ZIKV replication was initially detected in the spleen but subsequently spread to the brain with concomitant reduction of the virus in the spleen in the infected mice. Furthermore, ZIKV could be transmitted from mosquitoes to Stat1-/- mice back to mosquitoes and then to naïve Stat1-/- mice. The 50% mosquito infectious dose of viremic Stat1-/- mouse blood was close to 810 focus-forming units (ffu)/ml. Our further studies indicated that the activation of macrophages and conventional dendritic cells were likely critical for the resolution of ZIKV infection. The newly developed mouse and mosquito transmission models for ZIKV infection will be useful for the evaluation of antiviral drugs targeting the virus, vector, and host.

Finger injuries are among the most common injuries treated in the emergency department. After surgical management, surgeons find that patients with finger injuries will sometimes experience severe tenderness when dressings are being changed. To reduce patients’ discomfort an easy-to-use tool for painless finger wound dressing has been developed.

Cholangiocarcinoma is a relatively uncommon but highly lethal malignancy. Improving outcomes in patients depends on earlier diagnosis and appropriate treatment; however, no satisfactory diagnostic biomarkers or targeted therapies are currently available. To address this shortcoming, we analyzed the transcriptomic datasets of cholangiocarcinoma from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and found that TESC is highly expressed in cholangiocarcinoma. Elevated cellular levels of TESC are correlated with larger tumor size and predict a poor survival outcome for patients. Knockdown of TESC via RNA interference suppresses tumor growth. RNA-sequencing analysis showed that silencing of TESC decreases the level of FOXM1, leading to cell cycle arrest. Correlation analysis revealed that the cellular level of TESC is correlated with that of FOXM1 in cholangiocarcinoma patients. We further observed that upon TGF-α induction, TESC is upregulated through the EGFR-STAT3 pathway and mediates TGF-α-induced tumor cell proliferation. In vivo experiments revealed that knockdown of TESC significantly attenuates tumor cell growth. Therefore, our data provide novel insight into TESC-mediated oncogenesis and reveal that TESC is a potential biomarker or serves as a therapeutic target for cholangiocarcinoma.

Bidens pilosa is commonly used as an herbal tea component or traditional medicine for treating several diseases, including diabetes. Polyacetylenes have two or more carbon–carbon triple bonds or alkynyl functional groups and are mainly derived from fatty acid and polyketide precursors. Here, we report the cloning of full-length cDNAs that encode Δ12-fatty acid acetylenase (designated BPFAA) and Δ12-oleate desaturase (designated BPOD) from B. pilosa, which we predicted to play a role in the polyacetylene biosynthetic pathway. Subsequently, expression vectors carrying BPFAA or BPOD were constructed and transformed into B. pilosa via the Agrobacterium-mediated method. Genomic PCR analysis confirmed the presence of transgenes and selection marker genes in the obtained transgenic lines. The copy numbers of transgenes in transgenic lines were determined by Southern blot analysis. Furthermore, 4–5 FAA genes and 2–3 OD genes were detected in wild-type (WT) plants. Quantitative real time-PCR revealed that some transgenic lines had higher expression levels than WT. Western blot analysis revealed OD protein expression in the selected transformants. High-performance liquid chromatography profiling was used to analyze the seven index polyacetylenic compounds, and fluctuation patterns were found.