Characterization of N-glycosylation and its functional role in SIDT1-Mediated RNA uptake.

The mammalian SID-1 transmembrane family members, SIDT1 and SIDT2, are multipass transmembrane proteins that mediate the cellular uptake and intracellular trafficking of nucleic acids, playing important roles in the immune response and tumorigenesis. Previous work has suggested that human SIDT1 and SIDT2 are N-glycosylated, but the precise site-specific N-glycosylation information and its functional contribution remain unclear. In this study, we use high-resolution liquid chromatography tandem mass spectrometry to comprehensively map the N-glycosites and quantify the N-glycosylation profiles of SIDT1 and SIDT2. Further molecular mechanistic probing elucidates the essential role of N-linked glycans in regulating cell surface expression, RNA binding, protein stability, and RNA uptake of SIDT1. Our results provide crucial information about the potential functional impact of N-glycosylation in the regulation of SIDT1-mediated RNA uptake and provide insights into the molecular mechanisms of this promising nucleic acid delivery system with potential implications for therapeutic applications.

Molecular electronics sensors on a scalable semiconductor chip: A platform for single-molecule measurement of binding kinetics and enzyme activity.

For nearly 50 years, the vision of using single molecules in circuits has been seen as providing the ultimate miniaturization of electronic chips. An advanced example of such a molecular electronics chip is presented here, with the important distinction that the molecular circuit elements play the role of general-purpose single-molecule sensors. The device consists of a semiconductor chip with a scalable array architecture. Each array element contains a synthetic molecular wire assembled to span nanoelectrodes in a current monitoring circuit. A central conjugation site is used to attach a single probe molecule that defines the target of the sensor. The chip digitizes the resulting picoamp-scale current-versus-time readout from each sensor element of the array at a rate of 1,000 frames per second. This provides detailed electrical signatures of the single-molecule interactions between the probe and targets present in a solution-phase test sample. This platform is used to measure the interaction kinetics of single molecules, without the use of labels, in a massively parallel fashion. To demonstrate broad applicability, examples are shown for probe molecule binding, including DNA oligos, aptamers, antibodies, and antigens, and the activity of enzymes relevant to diagnostics and sequencing, including a CRISPR/Cas enzyme binding a target DNA, and a DNA polymerase enzyme incorporating nucleotides as it copies a DNA template. All of these applications are accomplished with high sensitivity and resolution, on a manufacturable, scalable, all-electronic semiconductor chip device, thereby bringing the power of modern chips to these diverse areas of biosensing.

Method of generating speckle patterns for digital image correlation based on modified Conway's Game of Life.

The measurement accuracy of digital image correlation (DIC) is influenced by the quality of the speckle pattern. Although various models for generating random speckle patterns have been well discussed, obtaining appropriate speckle images with isotropic quality and performance could be a challenging issue in DIC. In this paper, we propose a novel (to our knowledge) method for generating speckle patterns based on modified Conway's game of life (GoL). By sequentially assembling the speckle patterns generated from the modified GoL, we produced the GoL speckle image. Then, verification and comparison experiments were conducted through pure in-plane translations. The results show that the generated speckle image which was resized with k s=6& k r=2 processing and subsequently fuzzified using a Gaussian filter, produces the best accuracy for DIC measurement. Furthermore, based on the rigid body in-plane rotation displacement tests in the physical experimental results of three different speckle images, the GoL speckle generated from our proposed method shows the smallest measurement error. This indicates that the proposed speckle patterns generating method could provide a new type of speckle pattern with better quality and accuracy.

Mechanism of an RBM-targeted rabbit monoclonal antibody 9H1 neutralizing SARS-CoV-2.

The COVID-19 pandemic, caused by SARS-CoV-2, has led to over 750 million infections and 6.8 million deaths worldwide since late 2019. Due to the continuous evolution of SARS-CoV-2, many significant variants have emerged, creating ongoing challenges to the prevention and treatment of the pandemic. Therefore, the study of antibody responses against SARS-CoV-2 is essential for the development of vaccines and therapeutics. Here we perform single particle cryo-electron microscopy (cryo-EM) structure determination of a rabbit monoclonal antibody (RmAb) 9H1 in complex with the SARS-CoV-2 wild-type (WT) spike trimer. Our structural analysis shows that 9H1 interacts with the receptor-binding motif (RBM) region of the receptor-binding domain (RBD) on the spike protein and by directly competing with angiotensin-converting enzyme 2 (ACE2), it blocks the binding of the virus to the receptor and achieves neutralization. Our findings suggest that utilizing rabbit-derived mAbs provides valuable insights into the molecular interactions between neutralizing antibodies and spike proteins and may also facilitate the development of therapeutic antibodies and expand the antibody library.

MiR-302c-5p affects the stemness and cisplatin resistance of nasopharyngeal carcinoma cells by regulating HSP90AA1.

Nasopharyngeal carcinoma (NPC) is one of the most frequent malignant tumors diagnosed in China. Cisplatin is one of the most commonly used anticancer drugs containing platinum in combined chemotherapy. The molecular mechanism of NPC is still largely unknown, and we aim to spare no effort to elucidate it. Normal human nasopharyngeal epithelial cells and NPC cell lines were cultured. The expression levels of miR-302c-5p and HSP90AA1 were detected with quantitative real-time PCR. Western blotting was used to analyze levels of the HSP90AA1, protein kinase B (AKT), p-AKT, CD44 and SOX2 proteins. The interaction between miR-302c-5p and HSP90AA1 was detected using a luciferase reporter assay. The bicinchoninic acid assay was used to observe cisplatin resistance in NPC cells. Our records confirmed that the expression of miR-302c-5p was substantially reduced and HSP90AA1 was increased in NPC cells. Additionally, miR-302c-5p inhibited cisplatin resistance and the traits of stem cells in NPC. A luciferase assay confirmed that miR-302c-5p is bound to HSP90AA1. Overexpression of HSP90AA1 may reverse the effects of overexpressed miR-302c-5p and inhibit cisplatin resistance and stem cell traits of NPC. This study investigated whether miR-302c-5p inhibited the AKT pathway by regulating HSP90AA1 expression and altered the resistance of NPC cells to cisplatin and the traits of tumor stem cells, which has not yet been reported.

Structural and mechanistic insights into STIM1-mediated initiation of store-operated calcium entry.

Stromal interaction molecule-1 (STIM1) activates store-operated Ca2+ entry (SOCE) in response to diminished luminal Ca2+ levels. Here, we present the atomic structure of the Ca2+-sensing region of STIM1 consisting of the EF-hand and sterile alpha motif (SAM) domains (EF-SAM). The canonical EF-hand is paired with a previously unidentified EF-hand. Together, the EF-hand pair mediates mutually indispensable hydrophobic interactions between the EF-hand and SAM domains. Structurally critical mutations in the canonical EF-hand, "hidden" EF-hand, or SAM domain disrupt Ca2+ sensitivity in oligomerization via destabilization of the entire EF-SAM entity. In mammalian cells, EF-SAM destabilization mutations within full-length STIM1 induce punctae formation and activate SOCE independent of luminal Ca2+. We provide atomic resolution insight into the molecular basis for STIM1-mediated SOCE initiation and show that the folded/unfolded state of the Ca2+-sensing region of STIM is crucial to SOCE regulation.

Multivalent assembly of KRAS with the RAS-binding and cysteine-rich domains of CRAF on the membrane.

Membrane anchoring of farnesylated KRAS is critical for activation of RAF kinases, yet our understanding of how these proteins interact on the membrane is limited to isolated domains. The RAS-binding domain (RBD) and cysteine-rich domain (CRD) of RAF engage KRAS and the plasma membrane, unleashing the kinase domain from autoinhibition. Due to experimental challenges, structural insight into this tripartite KRAS:RBD-CRD:membrane complex has relied on molecular dynamics simulations. Here, we report NMR studies of the KRAS:CRAF RBD-CRD complex. We found that the nucleotide-dependent KRAS-RBD interaction results in transient electrostatic interactions between KRAS and CRD, and we mapped the membrane interfaces of the CRD, RBD-CRD, and the KRAS:RBD-CRD complex. RBD-CRD exhibits dynamic interactions with the membrane through the canonical CRD lipid-binding site (CRD ß7-8), as well as an alternative interface comprising ß6 and the C terminus of CRD and ß2 of RBD. Upon complex formation with KRAS, two distinct states were observed by NMR: State A was stabilized by membrane association of CRD ß7-8 and KRAS α4-α5 while state B involved the C terminus of CRD, ß3-5 of RBD, and part of KRAS α5. Notably, α4-α5, which has been proposed to mediate KRAS dimerization, is accessible only in state B. A cancer-associated mutation on the state B membrane interface of CRAF RBD (E125K) stabilized state B and enhanced kinase activity and cellular MAPK signaling. These studies revealed a dynamic picture of the assembly of the KRAS-CRAF complex via multivalent and dynamic interactions between KRAS, CRAF RBD-CRD, and the membrane.

Mid-infrared optical switches enabled by metal-organic frameworks for compact high-power nanosecond laser sources at 3 µm.

Pulsed lasers operating in the mid-infrared are of great importance for numerous applications in spectroscopy, medical surgery, laser processing, and communications. In spite of recent advances with mid-infrared gain platforms, the lack of a capable pulse generation mechanism hinders the development of compact mid-infrared pulsed laser source. Here we show that MIL-68(Al) and MIL-68(Fe), which are aluminum- and iron- based metal-organic frameworks (MOFs) with ordered atoms distribution and periodic mesoporous structure, constitute exceptional optical switches for the mid-infrared. We fabricated the MIL-68(Al) and MIL-68(Fe) via hydrothermal method and prepared reflection-type MIL-68(Al)- and MIL-68(Fe)- saturable absorber mirrors (SAMs). By employing the as-prepared SAMs in the laser cavities, we achieved high-power nanosecond Q-switched fiber lasers at 2.8 µm. Especially, the average output power and pulse duration of the MIL-68(Al) Q-switched fiber laser reached 809.1 mW and 567 ns, respectively. To the best of our knowledge, this is the first time to demonstrate that MIL-68(M) can be efficient optical switches for 3-µm mid-IR laser pulses generation. Our findings reveal that MIL-68(M) is promising saturable absorber for compact and high-performance mid-infrared pulsed lasers.

Long-term stable platinum diselenide for nanosecond pulse generation in a 3-µm mid-infrared fiber laser.

In this paper, we fabricate the bulk-like multilayer platinum diselenide (PtSe2) and employ it as saturable absorber (SA) for a passively Q-switched fiber laser operating at 2865 nm for the first time, to the best of our knowledge. The nonlinear optical measurements of the bulk-like multilayer PtSe2 reveal efficient saturable absorption property at around 3 µm showing a modulation depth of 8.54% and a saturation intensity of 0.074 GW/cm2. By introducing the bulk-like PtSe2-SA into the Ho3+/Pr3+ co-doped ZBLAN fiber laser, stable Q-switched pulses with a duration as short as 620 ns are achieved at the pulse repetition rate of 238.1 kHz. The maximum average power is 93 mW, corresponding to a peak power of 0.63 W. The excellent long-term stability of the PtSe2-SA was also verified utilizing the same experimental setup after 40 days of ambient storage of the PtSe2 sample. The results not only validate the excellent nonlinear optical performance of PtSe2, but also indicate that the bulk-like PtSe2 is a promising long-term stable SA material under ambient conditions for nanosecond pulse generation in the 3-µm mid-infrared spectral region.

Two Distinct Structures of Membrane-Associated Homodimers of GTP- and GDP-Bound KRAS4B Revealed by Paramagnetic Relaxation Enhancement.

KRAS homo-dimerization has been implicated in the activation of RAF kinases, however, the mechanism and structural basis remain elusive. We developed a system to study KRAS dimerization on nanodiscs using paramagnetic relaxation enhancement (PRE) NMR spectroscopy, and determined distinct structures of membrane-anchored KRAS dimers in the active GTP- and inactive GDP-loaded states. Both dimerize through an α4-α5 interface, but the relative orientation of the protomers and their contacts differ substantially. Dimerization of KRAS-GTP, stabilized by electrostatic interactions between R135 and E168, favors an orientation on the membrane that promotes accessibility of the effector-binding site. Remarkably, "cross"-dimerization between GTP- and GDP-bound KRAS molecules is unfavorable. These models provide a platform to elucidate the structural basis of RAF activation by RAS and to develop inhibitors that can disrupt the KRAS dimerization. The methodology is applicable to many other farnesylated small GTPases.

Correction to: Isoliquiritigenin Provides Protection and Attenuates Oxidative Stress-Induced Injuries via the Nrf2-ARE Signaling Pathway After Traumatic Brain Injury.

The original version of this article unfortunately contained a mistake. The Fluorescence Immunoassays text written in Materials and Methods section and Fig. 1i, j is incorrect. In Fig. 1j, the images corresponding to Sham and TBI + ILG are incorrect. In Fig. 1i the figure caption "TBI + EDA" are incorrect. The corrected text and Fig. 1i, j are given below.

A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data.

BACKGROUND: The rapid deterioration observed in the condition of some hospitalized patients can be attributed to either disease progression or imperfect triage and level of care assignment after their admission. An early warning system (EWS) to identify patients at high risk of subsequent intrahospital death can be an effective tool for ensuring patient safety and quality of care and reducing avoidable harm and costs. OBJECTIVE: The aim of this study was to prospectively validate a real-time EWS designed to predict patients at high risk of inpatient mortality during their hospital episodes. METHODS: Data were collected from the system-wide electronic medical record (EMR) of two acute Berkshire Health System hospitals, comprising 54,246 inpatient admissions from January 1, 2015, to September 30, 2017, of which 2.30% (1248/54,246) resulted in intrahospital deaths. Multiple machine learning methods (linear and nonlinear) were explored and compared. The tree-based random forest method was selected to develop the predictive application for the intrahospital mortality assessment. After constructing the model, we prospectively validated the algorithms as a real-time inpatient EWS for mortality. RESULTS: The EWS algorithm scored patients' daily and long-term risk of inpatient mortality probability after admission and stratified them into distinct risk groups. In the prospective validation, the EWS prospectively attained a c-statistic of 0.884, where 99 encounters were captured in the highest risk group, 69% (68/99) of whom died during the episodes. It accurately predicted the possibility of death for the top 13.3% (34/255) of the patients at least 40.8 hours before death. Important clinical utilization features, together with coded diagnoses, vital signs, and laboratory test results were recognized as impactful predictors in the final EWS. CONCLUSIONS: In this study, we prospectively demonstrated the capability of the newly-designed EWS to monitor and alert clinicians about patients at high risk of in-hospital death in real time, thereby providing opportunities for timely interventions. This real-time EWS is able to assist clinical decision making and enable more actionable and effective individualized care for patients' better health outcomes in target medical facilities.

Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine.

BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. Early detection of individuals at risk of lung cancer is critical to reduce the mortality rate. OBJECTIVE: The aim of this study was to develop and validate a prospective risk prediction model to identify patients at risk of new incident lung cancer within the next 1 year in the general population. METHODS: Data from individual patient electronic health records (EHRs) were extracted from the Maine Health Information Exchange network. The study population consisted of patients with at least one EHR between April 1, 2016, and March 31, 2018, who had no history of lung cancer. A retrospective cohort (N=873,598) and a prospective cohort (N=836,659) were formed for model construction and validation. An Extreme Gradient Boosting (XGBoost) algorithm was adopted to build the model. It assigned a score to each individual to quantify the probability of a new incident lung cancer diagnosis from October 1, 2016, to September 31, 2017. The model was trained with the clinical profile in the retrospective cohort from the preceding 6 months and validated with the prospective cohort to predict the risk of incident lung cancer from April 1, 2017, to March 31, 2018. RESULTS: The model had an area under the curve (AUC) of 0.881 (95% CI 0.873-0.889) in the prospective cohort. Two thresholds of 0.0045 and 0.01 were applied to the predictive scores to stratify the population into low-, medium-, and high-risk categories. The incidence of lung cancer in the high-risk category (579/53,922, 1.07%) was 7.7 times higher than that in the overall cohort (1167/836,659, 0.14%). Age, a history of pulmonary diseases and other chronic diseases, medications for mental disorders, and social disparities were found to be associated with new incident lung cancer. CONCLUSIONS: We retrospectively developed and prospectively validated an accurate risk prediction model of new incident lung cancer occurring in the next 1 year. Through statistical learning from the statewide EHR data in the preceding 6 months, our model was able to identify statewide high-risk patients, which will benefit the population health through establishment of preventive interventions or more intensive surveillance.

Isoliquiritigenin Provides Protection and Attenuates Oxidative Stress-Induced Injuries via the Nrf2-ARE Signaling Pathway After Traumatic Brain Injury.

Traumatic brain injury (TBI) is a serious public health and medical problem worldwide. Oxidative stress plays a vital role in the pathogenesis of TBI. Nuclear factor erythroid 2-related factor 2 (Nrf2), an important factor in the cellular defense against oxidative stress, is activated following TBI. In this study, the protective effects of Isoliquiritigenin (ILG), a promising antioxidant stress drug, was evaluated as a protective agent against TBI. In a mouse model of controlled cortical impact Injury, we found that the ILG administration reduced the Garcia neuroscore, injury histopathology, brain water content, cerebral vascular permeability, the expression of cleaved caspase3, aquaporin-4, glial fibrillary acidic protein and the increased the expression of neurofilament light chain protein, indicating the protective effects against TBI in vivo. ILG treatment after TBI also restored the oxidative stress and promoted the Nrf2 protein transfer from the cytoplasm to the nucleus. We then used Nrf2-/- mice to test the protective effect of Nrf2 during ILG treatment of TBI. Our findings indicated that Nrf2-/- mice had greater brain injury and oxidative stress than wild-type (WT) mice and ILG was less effective at inhibiting oxidative stress and repairing the brain injury than in the WT mice. In vitro studies in SY5Y cells under oxygen glucose deprivation/re-oxygenation stimulation yielded results that were consistent with those obtained in vivo showing that ILG promotes Nrf2 protein transfer from the cytoplasm to the nucleus. Taken together, our findings demonstrate that Nrf2 is an important protective factor against TBI-induced injuries, which indicates that the protective effects of ILG are mediated by inhibiting oxidative stress after TBI via a mechanism that involves the promotion of Nrf2 protein transfer from the cytoplasm to the nucleus.

Assessing Statewide All-Cause Future One-Year Mortality: Prospective Study With Implications for Quality of Life, Resource Utilization, and Medical Futility.

BACKGROUND: For many elderly patients, a disproportionate amount of health care resources and expenditures is spent during the last year of life, despite the discomfort and reduced quality of life associated with many aggressive medical approaches. However, few prognostic tools have focused on predicting all-cause 1-year mortality among elderly patients at a statewide level, an issue that has implications for improving quality of life while distributing scarce resources fairly. OBJECTIVE: Using data from a statewide elderly population (aged ≥65 years), we sought to prospectively validate an algorithm to identify patients at risk for dying in the next year for the purpose of minimizing decision uncertainty, improving quality of life, and reducing futile treatment. METHODS: Analysis was performed using electronic medical records from the Health Information Exchange in the state of Maine, which covered records of nearly 95% of the statewide population. The model was developed from 125,896 patients aged at least 65 years who were discharged from any care facility in the Health Information Exchange network from September 5, 2013, to September 4, 2015. Validation was conducted using 153,199 patients with same inclusion and exclusion criteria from September 5, 2014, to September 4, 2016. Patients were stratified into risk groups. The association between all-cause 1-year mortality and risk factors was screened by chi-squared test and manually reviewed by 2 clinicians. We calculated risk scores for individual patients using a gradient tree-based boost algorithm, which measured the probability of mortality within the next year based on the preceding 1-year clinical profile. RESULTS: The development sample included 125,896 patients (72,572 women, 57.64%; mean 74.2 [SD 7.7] years). The final validation cohort included 153,199 patients (88,177 women, 57.56%; mean 74.3 [SD 7.8] years). The c-statistic for discrimination was 0.96 (95% CI 0.93-0.98) in the development group and 0.91 (95% CI 0.90-0.94) in the validation cohort. The mortality was 0.99% in the low-risk group, 16.75% in the intermediate-risk group, and 72.12% in the high-risk group. A total of 99 independent risk factors (n=99) for mortality were identified (reported as odds ratios; 95% CI). Age was on the top of list (1.41; 1.06-1.48); congestive heart failure (20.90; 15.41-28.08) and different tumor sites were also recognized as driving risk factors, such as cancer of the ovaries (14.42; 2.24-53.04), colon (14.07; 10.08-19.08), and stomach (13.64; 3.26-86.57). Disparities were also found in patients' social determinants like respiratory hazard index (1.24; 0.92-1.40) and unemployment rate (1.18; 0.98-1.24). Among high-risk patients who expired in our dataset, cerebrovascular accident, amputation, and type 1 diabetes were the top 3 diseases in terms of average cost in the last year of life. CONCLUSIONS: Our study prospectively validated an accurate 1-year risk prediction model and stratification for the elderly population (≥65 years) at risk of mortality with statewide electronic medical record datasets. It should be a valuable adjunct for helping patients to make better quality-of-life choices and alerting care givers to target high-risk elderly for appropriate care and discussions, thus cutting back on futile treatment.

Target Identification of Kinase Inhibitor Alisertib (MLN8237) by Using DNA-Programmed Affinity Labeling.

Accurate identification of the molecular targets of bioactive small molecules is a highly important yet challenging task in biomedical research. Previously, a method named DPAL (DNA-programmed affinity labeling) for labeling and identifying the cellular targets of small molecules and nucleic acids was developed. Herein, DPAL is applied for the target identification of Alisertib (MLN8237), which is a highly specific aurora kinase A (AKA) inhibitor and a drug candidate being tested in clinical trials for cancer treatment. Apart from the well-established target of AKA, several potential new targets of MLN8237 were identified. Among them, p38 mitogen-activated protein kinase (p38) and laminin receptor (LAMR) were validated to be implicated in the anticancer activities of MLN8237. Interestingly, these new targets were not identified with non-DNA-based affinity probes. This work may facilitate an understanding of the molecular basis of the efficacy and side effects of MLN8237 as a clinical drug candidate. On the other hand, this work has also demonstrated that the method of DPAL could be a useful tool for target identification of bioactive small molecules.

A Novel Monopulse Technique for Adaptive Phased Array Radar.

The monopulse angle measuring technique is widely adopted in radar systems due to its simplicity and speed in accurately acquiring a target's angle. However, in a spatial adaptive array, beam distortion, due to adaptive beamforming, can result in serious deterioration of monopulse performance. In this paper, a novel constrained monopulse angle measuring algorithm is proposed for spatial adaptive arrays. This algorithm maintains the ability to suppress the unwanted signals without suffering from beam distortion. Compared with conventional adaptive monopulse methods, the proposed algorithm adopts a new form of constraint in forming the difference beam with the merit that it is more robust in most practical situations. At the same time, it also exhibits the simplicity of one-dimension monopulse, helping to make this algorithm even more appealing to use in adaptive planar arrays. The theoretical mean and variance of the proposed monopulse estimator is derived for theoretical analysis. Mathematical simulations are formulated to demonstrate the effectiveness and advantages of the proposed algorithm. Both theoretical analysis and simulation results show that the proposed algorithm can outperform the conventional adaptive monopulse methods in the presence of severe interference near the mainlobe.

Cerebrospinal fluid protein dynamic driver network: At the crossroads of brain tumorigenesis.

To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In our controlled rat model study, matched ENU- and saline-exposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar.

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar's estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method.

A coiled-coil clamp controls both conformation and clustering of stromal interaction molecule 1 (STIM1).

Store-operated Ca(2+) entry, essential for the adaptive immunity, is initiated by the endoplasmic reticulum (ER) Ca(2+) sensor STIM1. Ca(2+) entry occurs through the plasma membrane resident Ca(2+) channel Orai1 that directly interacts with the C-terminal STIM1 domain, named SOAR/CAD. Depletion of the ER Ca(2+) store controls this STIM1/Orai1 interaction via transition to an extended STIM1 C-terminal conformation, exposure of the SOAR/CAD domain, and STIM1/Orai1 co-clustering. Here we developed a novel approach termed FRET-derived Interaction in a Restricted Environment (FIRE) in an attempt to dissect the interplay of coiled-coil (CC) interactions in controlling STIM1 quiescent as well as active conformation and cluster formation. We present evidence of a sequential activation mechanism in the STIM1 cytosolic domains where the interaction between CC1 and CC3 segment regulates both SOAR/CAD exposure and CC3-mediated higher-order oligomerization as well as cluster formation. These dual levels of STIM1 auto-inhibition provide efficient control over the coupling to and activation of Orai1 channels.