Air quality around the globe is declining and public health is seriously threatened by indoor air pollution. Typically, indoor air pollutants are composed of a series of volatile organic compounds (VOCs) that are generally harmful to the human body, especially VOCs with low molecular weights (less than 100 Da). Moreover, in some situations, more than one type of VOC is present; thus, a device that can detect one or more VOCs simultaneously would be most beneficial. Here, we synthesized a sensor array with 4 units to detect 4 VOCs: acetone (unit 1), benzene (unit 2), methanol (unit 3) and formaldehyde (unit 4) simultaneously. All units were simultaneously exposed to 2.5 ppm of all four VOCs. The sensitivity of unit 1 was 14.67 for acetone and less than 2.54 for the other VOCs. The sensitivities of units 2, 3 and 4 to benzene, methanol and formaldehyde were 2 18.64, 20.98 and 17.26, respectively, and less than 4.01 for the other VOCs. These results indicated that the sensor array exhibited good selectivity and could be used for the real-time monitoring of indoor air quality. Thus, this device will be useful in situations requiring the simultaneous detection of multiple VOCs. Indoor environmental pollution caused by VOCs has become an important issue. For example, acetone, which is a widely used solvent in industry and laboratories, can volatilize easily and affect human health when its concentration exceeds 173 ppm4. Additionally, benzene and its homologs, such as toluene and xylene, are known to be toxic to the hematopoietic system (hematotoxicity) and to cause leukemia5. Methanol possesses strong toxicity, especially to the blood and nervous system. Furthermore, previous studies have shown that methanol is potentially harmful to human optic nerves and retinas7. Formaldehyde has been classified as a mutagen and possible human carcinogen by both the US Environmental Protection Agency and the World Health Organization because of its toxicity, anaphylactic potential and harmful accumulation in the environment9. Effort has been expended to detect these harmful VOCs, and some of the relevant works are summarized in Table 3 (ALFO) and can thus be fabricated on the same substrate, which greatly contributes to the significance and convenience of the application of the device.It is an indisputable fact that volatile organic compounds (VOCs), which are common air pollutants, are harmful to the human body3 (LFO) is a common perovskite-type oxide that exhibits semiconducting behavior10 and is a promising material with an abundance of functionalities, especially in the field of gas sensing. LFO possesses great potential for detecting pollutant gases because of its specific chemical and physical characteristics, including its large surface area, rich active oxygen lattice, good thermostability11, controllable structure12, and strong reducibility17. Thus, LFO is a more attractive gas-sensing material than other metal oxides. In addition, when LFO is doped with Ag (ALFO), some Ag is present that can act as a catalyst in the matrix. Indeed, some of the Ag fills areas between the grains of the matrix and works to decrease the contact potential barrier and enhance the interfacial effects, leading to a lower resistance, and thus, a lower operating temperature18. Therefore, ALFO was selected as the material for the units developed in this study.In contrast to some single-metal oxide semiconductors, LaFeO22. In this approach, the shape and functionality of a template can be transcribed onto microporous materials. The configuration of the functional groups in the template can be memorized within the host polymers. Today, this field is dominated by the recognition and separation of organic macromolecules, such as proteins21 (molecular weight: 40–220 kDa) and enzymes22 (130–140 kDa). However, for small organic molecules, such as VOCs (molecular weight <100 Da), no relevant research has yet been reported.Most importantly, the selectivity of ALFO toward acetone, benzene, methanol and formaldehyde can be modulated via the molecular imprinting technique (MIT). The MIT results in a predesigned molecular recognition capability that can be used to build robust sensorsBased on the MIT, using acetone as a template and choosing an appropriate acetone-related functional monomer, ALFO was prepared as an acetone gas-sensing material (hereafter abbreviated as Mater.a). Similarly, using benzene, methanol and formaldehyde as templates and choosing appropriate functional monomers, ALFO can be prepared as benzene (Mater.b), methanol (Mater.m) and formaldehyde (Mater.f) gas-sensing material. Subsequently, the four materials were brush-coated onto a sensor array, as shown in Fig. 23, as a result, template, functional monomer and initiator could not be detected either. The microtopographies of Mater.a, Mater.b, Mater.m and Mater.f were spherical and uniform in size, with particle sizes in the range of 20–70 nm  spectra of ALFO, acetone, benzene, methanol and formaldehyde and the related functional monomers N,N’-methylenebisacrylamide (MBA), formaldehyde (HCHO), methacrylic acid (MAA) and acrylamide (AM) were obtained  to that in air (Ra). After the ALFO was polymerized with MBA, the gas-sensing mechanism was similar to that of LFO because LFO was the only phase in Mater.a 3·6H2O, 10.0 mmol of Fe(NO3)3·9H2O and 10.0 mmol of citrate were dissolved in 100 mL of distilled water to form solution A. AgNO3 (0.1 mmol) was dissolved in 10 mL of distilled water and added dropwise (12 drops/min) to solution A. Subsequently, polyethylene glycol was added. The final mixed solution was stirred at 80 °C for 8 h and then placed in a microwave chemical device  at 75 °C for 2 h. Thus, the ALFO sol was formed and used as a crosslinker in the molecular imprinting process.Preparation of the crosslinker: All the chemicals were analytical-grade reagents and were used as received from Tianjin Kermel Chemical Reagents Development Center. To prepare the crosslinker, 9.9 mmol of La. The final mixture was treated with ultrasonication for 30 min, stirred at 50 °C for 12 h under a nitrogen atmosphere under reflux and then dried. Finally, the xerogel was heated at 800 °C for 2 h, yielding Mater.a.Preparation of Mater.a: Acetone was used as the template, MBA was used as the functional monomer, azodiisobutyronitrile (AIBN) was used as the initiator and ALFO sol was used as the crosslinker. A schematic diagram of the hydrogen bonding between acetone and MBA is shown in Fig. b. Then, 1.0 mmol of AIBN was dissolved in 20 mL of benzene and mixed with solution Bb and ALFO sol (10.0 mmol). The final mixture was treated by ultrasonication for 30 min, stirred at 50 °C for 12 h under a nitrogen atmosphere under reflux and then dried. Finally, the xerogel was heated at 800 °C for 2 h, yielding Mater.b.Preparation of Mater.b: Benzene was used as the template, FA was used as the functional monomer, AIBN was used as the initiator and ALFO sol was used as the crosslinker. A schematic diagram of the hydrogen bonding between benzene and FA is shown in Fig. m. Then, 1.0 mmol of AIBN was dissolved in 20 mL of methanol and mixed with solution Bm and ALFO sol (10.0 mmol). The final mixture was treated with ultrasonication for 30 min, stirred at 50 °C for 12 h under a nitrogen atmosphere under reflux and then dried. Finally, the xerogel was heated at 800 °C for 2 h, yielding Mater.m.Preparation of Mater.m: Methanol was used as the template, MAA was used as the functional monomer, AIBN was used as the initiator and ALFO sol was used as the crosslinker. A schematic diagram of the hydrogen bonding between methanol and MAA is shown in Fig. f. Then, 1.0 mmol of AIBN was dissolved in 20 mL of formaldehyde and mixed with solution Bf and ALFO sol (10.0 mmol). The final mixture was treated with ultrasonication for 30 min, stirred at 50 °C for 12 h under a nitrogen atmosphere under reflux and then dried. Finally, the xerogel was heated at 800 °C for 2 h, yielding Mater.f.Preparation of Mater.f: Formaldehyde was used as the template, AM was used as the functional monomer, AIBN was used as the initiator and solution B was used as the crosslinker. A schematic diagram of the hydrogen bonding between formaldehyde and AM is shown in Fig. Preparation of the ALFO-based Mater.a, Mater.b, Mater.m, and Mater.f:The prepared materials were further mixed with distilled water and ground to form a paste, which was subsequently printed onto an alumina tube. Two Au electrodes were placed at the ends of the tube. The length of the alumina tube was 4 mm, and the diameter was 1.2 mm. To improve their stability and repeatability, the gas sensors were aged at 150 °C for 170 h in air. The gas-sensing properties were tested using a WS-30A gas senor tester. The relative humidity of the air chest was adjusted by injecting different amounts of water onto a hot plate. As the water was vaporized, the relative humidity changed and was monitored using a hygrometer.−1 to 400 cm−1. The particle morphology of each sample was determined by TEM (JEM-2100). The surface morphology and fracture surface were characterized by scanning electron microscopy . The pore size and Brunauer-Emmett-Teller (BET) surface area were analyzed using Quantachrome QuadRASORB-evo equipment.The XRD patterns were obtained for phase identification with a D/max23 diffractometer using Cu Kα1 radiation (λ = 1.54056 Å); the diffracted X-ray intensities were recorded as a function of 2θ. The accelerating voltage was 35 kV, the applied current was 25 mA, and the sample was scanned from 20° to 80° (2θ) in 0.02° steps. The functional groups were identified by FTIR (FTS-40), and each sample was embedded in a KBr pellet and scanned from 4000 cmSupporting Information


There was a significant improvement in THI and VAS scores after surgery . The decrease in THI scores in the low-frequency group was significantly larger than that of the mid- and high-frequency groups after surgery . The loudness of tinnitus decreased significantly after surgery (p = 0.031). Tinnitus in patients with VS improved after TLM. Patients with mid-/high-frequency tinnitus and louder tinnitus preoperatively seemed to have a worse prognosis than those with low-frequency and quieter tinnitus.We designed a prospective study to evaluate changes in tinnitus after vestibular schwannoma (VS) surgery. Subjects included 41 patients who were diagnosed with a VS and underwent translabyrinthine microsurgery (TLM) between January 2015 and May 2016. All patients underwent related examinations and were asked to answer the Tinnitus Handicap Inventory (THI) scale and a visual analog scale (VAS) of tinnitus severity both pre- and postoperatively. Of the 41 patients, 31 (75.6%) suffered from tinnitus before surgery. Microsurgery was associated with an overall decrease in tinnitus ( It is a frequent symptom of vestibular schwannoma (VS), occurring in more than half of all patients3. In the past, most surgeons aimed to completely remove the tumor while preserving facial nerve function and hearing; however, recently, more attention has been paid to the patient’s quality of life2. Because tinnitus can reduce the quality of life in these patients6, further evaluation of tinnitus in patients with VS should be considered.Tinnitus is the perception of sound in the absence of an external sound and usually results from a disorder of the somatosensory system or the auditory system7. These findings indicate that tinnitus originates in peripheral organs such as the cochlea or cochlear nerve9. However, some patients still suffer from tinnitus even after tumor removal and vestibulocochlear nerve section, which supports the theory that tinnitus is likely a symptom of central origin14. The objective of this study was to evaluate changes in tinnitus after VS microsurgery.Recently, several retrospective studies have been published focusing on changes in tinnitus after microsurgery; however, the results of these papers have varied. Most of these papers showed that tinnitus improved after surgery regardless of whether translabyrinthine microsurgery (TLM), a retrosigmoid approach, or a middle cranial fossa approach was used16 (see Supplementary Table). Patients without tinnitus have a handicap score of 0 on the THI, and higher THI scores correspond to worse tinnitus18. As in pain research19, visual analog scale (VAS) scales are increasingly being used to assess treatment-induced changes to the extent of annoyance caused by tinnitus20. With a VAS scale, patients self-grade the severity of tinnitus with possible scores ranging from 0 to 10 points; a score of 0 indicates no symptoms and a score of 10 indicates extremely loud tinnitus that seriously affects a patient’s daily life19.The Tinnitus Handicap Inventory (THI) is a reliable and valid measure of tinnitus-related handicap and is a questionnaire that is internationally acknowledgedThe study protocol was approved by the Institutional Review Board of the Affiliated Sixth People’s Hospital of Shanghai Jiao Tong University, and all methods were performed in accordance with the relevant guidelines and regulations. Informed consent for study participation was obtained from all participants.In total, 41 patients diagnosed with unilateral VS were enrolled in this prospective study between January 2015 and May 2016 in the Department of ENT Head and Neck Surgery at the Sixth People’s Hospital affiliated with Shanghai Jiao Tong University. These patients were treated with TLM because their preoperative hearing was already unserviceable, or the size of tumor was too large for hearing to be preserved. Patients who did not undergo surgery but were kept for observation and patients who underwent retrosigmoid or middle fossa approaches were excluded for this study. Microsurgery was performed by the same senior surgeon, and all patients underwent complete excision.21, tumor size, symptom duration, and the frequency and loudness of pre- and postoperative tinnitus were analyzed.All patients underwent pure-tone audiometry, acoustic immittance measurements, otoacoustic emissions measurements, tinnitogram, temporal bone computed tomography (CT), and internal auditory canal enhanced magnetic resonance imaging (MRI). Factors including preoperative pure-tone audiometry, postoperative facial function (House-Brackmann)22.Pure-tone averages (PTAs) were obtained by calculating the average thresholds at 500, 1000, and 2000 Hz23. All measurements were assessed by a senior radiologist and were checked by a senior otolaryngologist. For the tumor size criteria, we referred to the 2012 Acoustic Neuroma Association membership survey and divided the tumors into three groups by size: ≤1.5 cm, 1.6–2.5 cm and ≥2.6 cm24.All internal auditory canal enhanced MRI examinations were performed on an Achieva 3.0 T MRI system . In general, the cerebellopontine angle (CPA) along the long axis of the tumor was used as the maximum diameter, which was considered as the tumor size25. The acoustic signal was selected based on the tinnitus reported by the patient, and the types of acoustic signals were a pure-tone, narrow-band noise, pulse, warble tone and white noise. Then, the appropriate type was chosen according to the patient’s description. The matching process usually adopted the tonal debugging technique26 to adjust the initial test sound to the volume of the tinnitus. According to the pure-tone audiometry and experience of the technician, the participants were presented with a starting stimulus and asked if their tinnitus pitch was higher or lower. After the participants provided their answers, the frequency of the stimulus was adjusted. If the patient answered high, the frequency was increased by 50%; if the patient answered low, the frequency was reduced by 50%. If the tinnitus pitch was equal to the test sound, the test was stopped, and the last frequency was recorded. The test was repeated three times, and the average was calculated. The single ear loudness balance test was usually used to match loudness. Using the selected frequency of tinnitus, we matched the loudness to the individual’s tinnitus loudness in 1 dB steps by asking the participant whether the tinnitus was softer or louder27. For patients with hearing loss, we used the healthy ear to match. In the matching test, tinnitus was classified by frequency: ≤250 Hz, low-frequency; 500–2000 Hz, mid-frequency; and ≥4000 Hz, high-frequency22.Tinnitus frequency matching and tinnitus loudness matching were measured on tinnitograms17.The severity of tinnitus was evaluated using the THI and VAS scales. All enrolled patients were assessed via the THI and VAS scales pre- and postoperatively. The analysis of the THI scores used the total score rather than the subscalesData are presented as the mean ± standard deviation or the median (interquartile range).A postoperative follow-up was performed approximately one year after surgery; this included an interview regarding the patient’s postoperative state and changes in tinnitus and an internal auditory canal enhanced MRI. The follow-up rate was 100%.t-test, Spearman’s correlation analysis, Chi-square test, Fisher’s exact test and analysis of variance (ANOVA). For all analyses, p < 0.05 was considered to indicate statistical significance.Data were analyzed using SPSS . Data from survey responses were analyzed using Student’s p < 0.001).There were 41 patients included in our study, and no patients had lesions in both ears   (Table p = 0.011). We also found a strong correlation between the postoperative THI score and postoperative VAS score  , with a range of 6–82 in the preoperative tinnitus group. The average THI score was 14 (26) (median/interquartile range), with a range of 0–92, postoperatively. This indicates a general improvement between the pre- and postoperative THI scores (p < 0.001).In assessing the THI 20- point threshold as a significant change, we found that of these 31 patients with preoperative tinnitus, symptoms improved in 18 (58.1%), unchanged in 8 (25.8%), and worsened in 5 (16.1%) after surgery; all of these results were clinically significant (p = 0.785)   (Table p = 0.374)  , mid-frequency in 13 (41.9%), and high-frequency in 12 (38.7%). We found no significant correlation between the frequency of the preoperative tinnitus and preoperative THI  (Table p = 0.575)     dBHL, ranging from 20 to 80 dBHL. The postoperative tinnitus loudness ranged from 0 to 100 dBHL, with an average of 20 (74) dBHL. Thus, the loudness of tinnitus decreased significantly after surgery compared with the preoperative value ; 1.6–2.5 cm ; and ≥2.6 cm . Tumor size was correlated with the preoperative THI score and preoperative VAS score     cm. The patients were divided into three groups according to tumor size: ≤1.5 cm    . Age was not correlated with preoperative THI score or preoperative VAS score      cases and grade III in 5 (16.1%) cases; no correlation was observed between facial nerve function and the postoperative THI score or postoperative VAS score     months. The average symptom duration was 6 (60) months for patients with low-frequency tinnitus, 4 (119) months for patients with mid-frequency, and 12 (161) months for patients with high-frequency tinnitus. No significant differences in symptom duration were observed between the low-/mid-frequency and high-frequency groups  or improved (32.2%) for most patients after surgery, indicating a significant overall decrease in tinnitus via microsurgery. Patients with low-frequency and quieter tinnitus preoperatively seemed to have a better postoperative prognosis than those with mid-/high-frequency or louder tinnitus before the surgery.et al.17 reported that tinnitus was neither exacerbated nor relieved after TLM, while many others found that microsurgery improved tinnitus30, consistent with our observations. The underlying mechanisms are still unclear; however, several hypotheses have been proposed. First, the TLM surgical approach sacrifices inner ear and cochlear nerve function3, disrupting the central auditory conduction path. Second, cochlear or auditory nerve lesions can cause increases in the discharge rates of inner hair cells and nerve fibers, and the central auditory system cannot distinguish between pathological and normal physiological excitation and produces errors in hearing, resulting in tinnitus11. From this point of view, surgery may relieve the mechanical stimulation of the auditory nerve by the tumor, thus preventing the abnormal impulses and, consequently, eliminating tinnitus.Previous studies have demonstrated mixed surgical results regarding its effect on tinnitus. Baguley et al.3 reported that tinnitus disappeared or improved in most cases after the retrosigmoid approach and showed no difference in tinnitus incidence whether the vestibulocochlear nerve was resected or not. Park et al.2 suggested that cochlear nerve section may be beneficial for the improvement of postoperative tinnitus by comparing changes in tinnitus after TLM and gamma knife radiosurgery. In this study, the chosen surgery was the translabyrinthine approach because hearing preservation was not intended. During surgery, the cochlea nerve section was definite in all cases31 as suggested by Park et al.2, which may be the reason for the high rates of improvement in tinnitus. Although sectioning of the cochlear nerve creates a condition unsuitable for cochlear implantation32, either simultaneously or prospectively, a BAHA implant is a hearing solution for these patients33.Currently, no consensus exists on whether tinnitus relief is related to cochlear nerve dissection. Kameda 34. The author suggested that high-frequency tinnitus may be related to a longer duration and more severe injury and is therefore associated with greater difficulty in recovery. However, we found no significant relationship between the duration of tinnitus and the different frequencies.We found that the postoperative prognosis was better in patients with low-frequency tinnitus than in those with mid-/high-frequency tinnitus. However, the specific reasons and mechanisms for this finding remain unclear. Interestingly, a previous study found that among patients with sudden deafness accompanied by tinnitus, the rate of recovery was better for those with low-frequency tinnitus than those with high-frequency tinnitus19.The preoperative tinnitus loudness was significantly correlated with the postoperative tinnitus loudness in our cohort, i.e., greater loudness was correlated with greater difficulty in recovery. In theory, louder tinnitus has a greater impact on patients and therefore results in higher scores on the THI and VASet al.35, a 20- point or larger change is considered clinically significant at the 5% confidence level17. In this study, we found statistically significant changes in the THI score, considering any change in the THI to represent a change in tinnitus. Moreover, when we reassessed our results only considering a 20- point or larger change in the THI score, these changes were also statistically significant. Therefore, VS removal caused clinically relevant changes in our cohort.Based on the report by Newman 37. In this study, we found no correlation between them. Kohno et al.31 found that tinnitus appeared in one-fifth of the patients without preoperative tinnitus. We evaluated patients without preoperative tinnitus and found no new-onset tinnitus postoperatively.Whether the severity of tinnitus is associated with tumor size, age, preoperative pure-tone audiometry or postoperative facial nerve function remains controversial17. However, our study was a prospective study and focused exclusively on the translabyrinthine route. Baguley et al.17 and Alvarez et al.16 also focused on the translabyrinthine approach. They demonstrated a change in tinnitus only by the THI scale, whereas our study is the first clinical study to reveal correlations between the preoperative THI score, VAS score, loudness and changes in tinnitus postoperatively. These tests are not interchangeable. In addition, because this study had a relatively limited sample size of 41 patients, it remains possible that unperceived differences existed between the groups38.Some published findings are either retrospective studies or demonstrate that tinnitus improved after microsurgery regardless of which approach was usedTinnitus in patients with VS decreased after TLM surgery, as measured and cross-validated by three separate measures: THI, VAS, and tinnitus loudness matching. Patients with low-frequency and quieter tinnitus preoperatively seemed to have a better postoperative prognosis than those with mid-/high-frequency or louder tinnitus before the surgery.Supplementary Table


Early prediction of the potential for neurological recovery after resuscitation from cardiac arrest is difficult but important. Currently, no clinical finding or combination of findings are sufficient to accurately predict or preclude favorable recovery of comatose patients in the first 24 to 48 hours after resuscitation. Thus, life-sustaining therapy is often continued for several days in patients whose irrecoverable injury is not yet recognized. Conversely, early withdrawal of life-sustaining therapy increases mortality among patients who otherwise might have gone on to recover. In this work, we present Canonical Autocorrelation Analysis (CAA) and Canonical Autocorrelation Embeddings (CAE), novel methods suitable for identifying complex patterns in high-resolution multivariate data often collected in highly monitored clinical environments such as intensive care units. CAE embeds sets of datapoints onto a space that characterizes their latent correlation structures and allows direct comparison of these structures through the use of a distance metric. The methodology may be particularly suitable when the unit of analysis is not just an individual datapoint but a dataset, as for instance in patients for whom physiological measures are recorded over time, and where changes of correlation patterns in these datasets are informative for the task at hand.We present a proof of concept to illustrate the potential utility of CAE by applying it to characterize electroencephalographic recordings from 80 comatose survivors of cardiac arrest, aiming to identify patients who will survive to hospital discharge with favorable functional recovery. Our results show that with very low probability of making a Type 1 error, we are able to identify 32.5% of patients who are likely to have a good neurological outcome, some of whom have otherwise unfavorable clinical characteristics. Importantly, some of these had 5% predicted chance of favorable recovery based on initial illness severity measures alone. Providing this information to support clinical decision-making could motivate the continuation of life-sustaining therapies for these patients. Cardiac arrest is the most common cause of death in high-income nations . In the Unfortunately, accurate neurological prognostication after cardiac arrest is challenging, particularly in the first 3 to 5 days after resuscitation , 7, 8. AMultiple modalities which might inform early prognostication have been explored , 11, 12.We propose Canonical Autocorrelation Analysis (CAA) as a method for automated discovery of multiple-to-multiple correlation structures within a set of features. Through the introduction of a distance metric between CAA correlation structures, we are able to define Canonical Autocorrelation Embeddings (CAE), a feature space embedding in which each individual/object is represented by the set of its multivariate correlation structures. In this feature space embedding, traditional machine learning algorithms that rely on distance metrics, such as nonparametric clustering and k-nearest neighbors (k-nn), can be applied to compare correlation structures.This methodology is particularly fitting to tasks where multiple potentially correlated data points are recorded over space or time for each individual or unit of study. For example, in clinical medicine several vital signs or other physiological measures may be repeatedly sampled for each patient being monitored. Because physiological processes are interdependent and interact, analyzing the correlation structure between several such processes may reveal otherwise unrecognized patterns that may characterize the current state of the patient , 18. In Because of the difficulty identifying patients with potential for recovery and desire to limit futile care described above, patients may be at risk for withdrawal of life-sustaining therapy when their potential to recover goes unrecognized . To reduIn the remainder of this paper, Section 1 presents a brief review of related work. Section 2.1 discusses the task and data in more detail. In Section 2.1, CAA and CAE are introduced, as well as the use of a k-nn algorithm in the resulting embedded space. Section 3 contains the experimental results, Section 4 discusses our findings and Section 5 summarizes the conclusions and future work.ℓ1 variant of CCA, was proposed by [X and Y are two disjoint matrix representations for one set of objects, so that each matrix is using a strictly different set of variables to describe them. Assuming X and Y have been standardized, the constrained optimization problem is shown in c1 and c2 are small, solutions will be sparse and thus only a few features are correlated.Canonical Correlation Analysis (CCA) is a statistical method first introduced by , useful posed by , 24. ThiThe extension of Sparse CCA for discovery of multivariate correlations within a single set of features to study brain imaging has been previously explored in , 21. UsiCanonical Autocorrelation Analysis (CAA), the methodology we propose, is a generalized approach to discovering multiple-to-multiple correlations within a set of features. variance of data in one-dimensional projections, while CAA finds two-dimensional projections where correlation across two subsets of features is maximized. CAA specifically seeks projections composed by pairs of strongly correlated linear combinations of features, enabling discovery of hidden characteristic correlations in data, which cannot be easily found with other methods such as Sparse PCA. Other methods for finding sparse representations of data comprised in a single matrix include the well-known Sparse Principal Component Analysis (Sparse PCA). While CAA resembles Sparse PCA in the sense that it finds sparse representations of data contained in one matrix, Sparse PCA maximizes retained Extraction of informative projections has been tackled in the past , 26. OurThe comparison of correlation structures and principal components has been explored in the literature for decades. Most prominently,  discusseLearning to defer has been studied in the literature as a means to effectively combine algorithmic and human decision-making , 31. WheThis study was approved by the University of Pittsburgh Institutional Review Board with a waiver of informed consent. The data used in this case study are derived from 451 comatose survivors of cardiac arrest treated at a single academic medical center between 2010 and 2015 . For eacAlso available for each patient are time-invariant clinical characteristics and outcomes, including survival to hospital discharge. For those who lived, the quality of their functional recovery at discharge was measured using two standard outcome scales: Cerebral Performance Category and modified Rankin Scale. We considered “favorable recovery” to be either a Cerebral Performance Category of 1 or 2 or a modified Rankin Scale score of 0-2 at hospital discharge. For those who died, the proximate cause of death is known. X and Y. Applying Sparse CCA when X = Y results in solutions u = v, corresponding to Sparse PCA solutions for X [The goal of CAA is to find multivariate sparse correlations within a single set of variables. In the Sparse CCA framework, this could be understood as having identical matrices ns for X . We overL1 penalty when either u or v are fixed. Replacing the equality constraint by an inequality constraint gives a biconvex problem, while resulting in the same solution. Therefore, we can solve it through alternate convex search [This can be understood as a new generalization of the Penalized Matrix Decomposition . Note thx search , as showAlgorithm 1: CAA via alternate convex search1 Initialize v s.t. ||v||2 = 1;2repeat3  4  s.t. u||1 ≤ c1, 5  6  s.t. v||1 ≤ c1, 7untilu, vconverge;8d ← uTXTXv;u without loss of generality. For a detailed derivation see At each iteration, the resulting convex problem can be solved through the Karush-Kuhn-Tucker (KKT) conditions. The pseudo-code for solving the convex problems at each iteration of the alternate convex search is provided in Algorithm 2, where we solve for Algorithm 2: CAA alternate convex search iteration via KKT conditions12ifthen3  return4else5  Binary search to find λ2 s.t. 6  return7endXTX with a matrix from which the already found correlations are removed, as shown in d = uTXTXv.To find multiple pairs of CAA canonical vectors, Algorithm 1 can be repeated iteratively, replacing xi has a subset Si of associated indices of other features that should not be included as correlates of xi, the resulting optimization problem follows In order to enable the discovery of non-linear correlations by extending the feature space with subsequent powers of the original features , we modi1 penalty at each iteration of the biconvex optimization algorithm. Hence, the problem can still be solved as discussed above, with the only difference that the parameters of the soft-thresholding operator will change.The new constraint for disjoint support can still be understood as a weighted-Lu, v a CAA canonical space, and each CAA model may consist of one or more of such canonical spaces.CAA allows us to find bi-dimensional projections where the data closely follows a linear distribution. Each axis of these projections corresponds to a linear combination of the original features, and their respective coefficients are represented in a pair of vectors u||2 = ||v||2 = 1 ∀i, therefore, the distance between two CAA canonical spaces C1 and C2 can be defined as shown in Since the correlations discovered by CAA are defined by pairs of vectors in It is easy to show that this metric satisfies the necessary conditions for a well-defined distance, see Even though we believe that Having formulated a distance metric between pairs of CAA canonical spaces enables us to employ a range of distance-based machine learning algorithms, such as k-means, hierarchical clustering, or k-nn, to leverage similarities among correlation structures present in data. One additional complexity in our case is that each subset of data being compared may be represented by more than one CAA canonical space, and therefore more than one point in the embedding.k nearest neighbors, and then aggregating over all correlations associated to an object using log-odds, as shown in np,i,j denotes the class label of the jth neighbor of the ith correlation of patient p.This setting can be incorporated into the k-nn framework by calculating the class probability for each correlation structure through the votes of their t, so that log-odds are only calculated over those correlation structures with a class probability that is discriminative enough, as shown in k, indicating the number of neighbors, and t can be tuned through cross-validation.However, it is likely that some type of correlation structures will be common to both classes, while others are discriminative. To reduce noise and allow for those discriminative correlations to lead the decision, we incorporate a threshold Our principal goal is to help improve care given to comatose survivors of cardiac arrest through a decision support system that can boost the accuracy and timeliness of prognostication. To do so, we propose a new way to characterize patients using their latent multivariate correlation structures, and use the resulting featurization of data to build predictive models. The results presented in this section leverage data collected over a five year period at an academic medical center to provide a proof of concept of the proposed methodology.As seen in For each patient, their entire qEEG record is available, with lengths varying from less than an hour to more than a week. We aim to predict recovery as early as possible, but the earlier we attempt prediction, the more challenging it is. For the purposes of this experiment, we target prediction after 36 hours of monitoring. We use CAA to characterize a two hour epoch between hours 34 and 36. We choose 36 hours because we are interested in a period where the EEG is relatively static so that we do not need to account for temporal trends within the analyzed epoch. Clinically, patients are cooled down for 24 hours then allowed to rewarm at about 0.25-0.5C/hr. Both temperature and medications used to suppress shivering can alter the EEG . At 36 hR2 > 0.25. Moreover, to ensure that only reasonably close neighbors are used for matching, we prune connections by only considering distances smaller than k and t in an internal 10-fold cross-validation loop within each training fold, are presented in Figs In order to avoid spurious results, we only consider CAA canonical projections that yield correlations with logistic regression on sets and k-nn on sets, respectively. To emphasize the importance of considering a window of time rather than a snapshot, we also compare against the same two algorithms taking as input the last data point after 36 hours of monitoring, that is, the recording at one time step. We refer to this approach as logistic regression on points and k-nn on points, respectively. The parameters are chosen through 10-fold cross-validation. The results are included in Figs For baseline comparison, we use a popular approach: extract features based on metrics calculated over windows of time and apply standard classifiers to the resulting featurization , 36, 37.Finally, we apply the resulting system to those patients who were withdrawn from life-sustaining therapies. Amongst 31 patients who received life-sustaining therapies for at least 36 hours before withdrawal of life-sustaining therapies, five patients would have been marked by our classifier as very likely to recover at a threshold of FPR equal to 0.025.Recall that the proposed decision-support system is one that only makes recommendations when it has strong indications that the patient is likely to have a positive neurological recovery, and defers in all other cases. We evaluate the performance of the algorithm at the thresholds at which it would make recommendations, which we characterize through low false positive rates (FPR). The true positive rate (TPR) at a given FPR indicates what portion of positives–TPR—would be retrieved while assuring that no more than a given rate of negatives–FPR—will be incorrectly labeled as positive.Due to the gravity of errors in this scenario, the tolerance for false positives should be extremely low. Receiver Operator Curves (ROC) shown in Figs The results presented in Even though consensus guidelines advocate maintaining life-sustaining therapies for at least 72 hours after cardiac arrest , the buri), in a mild to moderate brain injury with good heart and lung function (category ii), in a mild to moderate brain injury but poor heart and/or lung activity (category iii), or severe brain injury with loss of some brainstem reflexes (category iv). While patients in category i have an associated probability of survival of 80%, and 60% probability of having a positive neurological recovery, patients in category iv have probabilities of 10%, and 5%, respectively. At a FPR lower than 0.025, the proposed methodology correctly identified a category iv patient who later went on to have a positive recovery. This constitutes a preliminary indication that the patterns of correlations in neurological activity measured with EEG constitute novel findings and have the potential to improve reliability of prognostication.To appropriately estimate the potential impact of such a decision support system in terms of lives saved, it is useful to compare against physicians’ assessments to validate if the predictions made with the proposed approach are non-redundant to what doctors already know. Each patient in our dataset is classified by Pittsburgh Cardiac Arrest Category, a 4-level, validated prognostic indicator assigned in the first six hours of their stay . This cliv. The remaining three received an initial Pittsburgh Cardiac Arrest Category of ii. While we do not have ground truth regarding counterfactuals of what would have happened if life-sustaining therapies had been continued for these patients, these results provide further indication that CAE is not simply leveraging patterns that are already being used by physicians.As discussed in Section 3, amongst those patients whose cause of death is withdrawal of life-sustaining therapy for perceived neurological prognosis, 5 out of 31 patients who received life-sustaining therapies for at least 36 hours would have been marked by our system as likely to have a positive recovery. Two of these patients had received a Pittsburgh Cardiac Arrest Category of bad outcome label. Meanwhile, the positive recovery label is sure to indicate positive neurological recovery (as well as positive recovery in other areas).While it would also be desirable to identify patients who have a very small probability of neurological recovery, we note that neither of the models would be able to provide confident recommendations to withdraw life-sustaining therapies while guaranteeing low false negative rates (FNR). A research direction that could further improve the performance of CAE is correlation trajectory modeling. While our model captures correlations observed within an interval of time, and in that sense it goes beyond a purely stationary approach, leveraging the sequential structures in data and using all data collected during a patients’ stay is desirable. Methodologically, this calls for the development of models for trajectory modeling of multivariate correlation structures. This could also encompass further exploration of additional distance metrics that could incorporate other types of information. By leveraging more information, such an approach would have the potential of providing earlier and more specific predictions.An additional direction for performance enhancement comes from the fact that our characterization of brain activity with CAA is motivated by the importance clinicians place on correlations. However, the correlations they know to be informative are across raw EEG channel measurements, and it is likely that at the current level of data aggregation, a big portion of the information may be to some extent obfuscated. This does not constitute a risk in terms of the validity of the results presented in this paper, but it means that further promising results may be expected from characterizing correlations in raw EEG signals. Such models could also lead to biological insights that may not be easily derived with the current approach.An important challenge that arises in this setting is the selective labels problem . SelectiCardiac arrest is a leading cause of death around the world, coma after cardiac arrest is common, and good neurological recovery is rare. Everyday, clinicians are tasked with making a prediction that determines whether they will continue life-sustaining therapies for their patients in coma or not. Motivated by the emphasis the clinicians place on potential informativeness of the correlation structures in EEG data, we have proposed a way to characterize and compare patients based on the latent structures of multivariate correlations, and use such information to predict positive neurological recovery. To do so, we have proposed a new formulation of Canonical Autocorrelation Analysis (CAA), a method that automatically finds subsets of features of data that form strong multiple-to-multiple correlations. We have also introduced Canonical Autocorrelation Embeddings (CAE) to enable the comparison of discovered correlation structures. CAE makes powerful and well established machine learning methodologies that rely on the use of distance metrics applicable to the task at hand.The results presented in this paper constitute a proof of concept. Future work involves collecting more data to train and validate the model. It is reasonable to believe that there may be a substantial heterogeneity across patients, hence experiments using more data of more subjects are a necessary next step. Applying CAE to the raw EEG channels rather than to the aggregated featurizations of data would also be interesting to explore once that data becomes available.In addition, we are developing machine learning methodology to tackle the selective labeling problem by incorporating clinicians’ domain knowledge while not reproducing their mistakes. Developing proper evaluation metrics to assess performance under selective labels, and finding ways to tackle the blindness that may result from this problem, is an important ingredient needed to successfully use machine learning to save lives in clinical settings.S1 TableComplete list of qEEG features available and used in this study.(PDF)Click here for additional data file.S1 FileSolution of CAA optimization problem via KKT conditions.(PDF)Click here for additional data file.S2 FileDiscussion of the relationship and differences between CAA and Sparse PCA.(PDF)Click here for additional data file.S3 FileProof of CAA well-defined distance metric.(PDF)Click here for additional data file.S4 FileDiscussion of why principal angles are not a well suited distance for CAA canonical spaces.(PDF)Click here for additional data file.


Aname and Teyl occurring in these local urban remnants. Local predator guilds were significantly influenced by leaf-litter cover (%) and proportion of surrounding parkland. Preference for spider vs. control models was consistent across all predator types , but specialist spider wasps (Pompilidae) only attacked spider models. Generalist predators  were more opportunistic. Lizards and rodents exhibit similar predation behaviour, indicating there may be some inter-specific competition. Invasive generalists (e. g. rodents) or urban adapters (e. g. corvids) are more likely to represent an increased threat to spiders than are co-evolved specialists (e.g. spider wasps).Predator-prey interactions may be altered under human-induced rapid environmental change, such as urbanisation. Extensive clearing in urban areas may leave short-range endemic species, such as mygalomorph spiders, more vulnerable to local extinction through predation in remaining remnants. Predation rates on Australian mygalomorph spiders were assessed using clay models of two size classes , during two time periods in 2016 . Size and phenology of models resembled the mygalomorph genera  Human-induced rapid environmental change, such as urban development, can place severe selective pressures on species to adapt to these changes, move away or persist in fragments or refugia within altered landscapes6.Since 1960 the global human population has dramatically increased and consolidated in urban centres7, some taxa, known as ‘urban exploiters’ e.g. rock pigeons (Columbia livia) and some rodents (e.g. Mus musculus and Rattus spp.) are found mainly in urban landscapes, where they subsist on anthropogenic resources. Other species, e.g. red foxes (Vulpes vulpes) globally8 or ravens (Corvus coronoides) and butcherbirds (Cracticus spp.)9 in Australia can be termed ‘urban adapters’ and benefit from resources such as anthropogenic food or shelter in urban areas but are not limited to urbanised areas. Urban adapters may have profound impact on their native prey species that still persist in patches of urban bushland. While urban adapters may thrive in various landscapes surrounding urban bushland, many native species are restricted to such patches. Negative impacts on native taxa may come from either novel threats (invasive species) or changes in predation behaviour of other native taxa through urbanisation.Response to urban environments varies amongst taxa. Although presence of many species is positively correlated with distance from urban environments10, and may be referred to as ‘urban engulfed’. These traits are present in many species of millipedes, snails, cicadas and mygalomorph spiders11. Such species are known as short-range endemics (SRE)12 and are of high conservation priority in Australia14.Taxa with comparatively low mobility, low-fecundity, poor dispersal and small geographic range may persist in very small natural habitat remnants in urban areas if the quality of the patch is maintained18. There is evidence that invasive rodents can have a severe effect on invertebrates on islands19, which may be analogous to predation in urban bushland fragments, as many native species may be confined to a single fragment. Reptiles, and lizards in particular, are predators of spiders and other invertebrates20. Reptile response in an urban environment seems to vary markedly between species, with some skinks being urban exploiters or adapters21. In Australia, predator-prey interactions involving invertebrates is less studied than vertebrates, probably due to taxonomic impediment and bias towards more charismatic subject species22. However, the predation and parasitisation of spiders by wasps , has been long known23. Exploring predator-prey interactions between urban wildlife will assist in understanding complex interactions, and how these may vary under HIREC.SRE species may face extinction as a result of the additional pressure of predation in small, fragmented populations. Differential predation of taxa across urban areas has not been well documented. Research addressing the threat associated with invasive rodents in Australia has often focused on various impacts on native taxa24. Subsequently, adult males emerge and roam to mate. This venture is a highly seasonal occurrence and appears to vary between species , roams during the summer months. A. mainae is the largest mygalomorph species of the region, reaching up to 5 cm in length. Males of most other species measure up to 2–3 cm in total body length24. These male dispersal events are likely to be the most dangerous times for mygalomorphs as they are exposed to a suite of predators to which they would not be exposed when in burrows. We aimed to test if there were selective or increased seasonal predation of male mygalomorphs while they are exposed on the surface during the mating season. Mygalomorph spider species have specialised microhabitats requirements. Hence, factors such as leaf litter, mid-storey and canopy cover may vary between species in their exposure to predators. In conjunction with other increased pressures present in an urban context, predation may decrease the chances of ongoing persistence of SREs.For most species in Perth, south-western Australia, male roaming occurs during periods of high humidity in winter, possibly due to physiological constraints27. As SRE endemic taxa are of high conservation priority and predation marks can be confidently identified on clay models, we decided this was the most effective and least harmful approach to test our hypotheses27. Our study is the first to use clay models to measure predation types, predation size and frequency on mygalomorph spiders. The questions we asked were:What are the local predator guilds?Is there evidence of competition between identified predator types?Is surrounding land-use correlated with guilds?(2)Is there a significant difference between predator preferences in terms of spider vs. control, size of model, and season?(3)Is predation frequency by identified predator types influenced by microhabitat variables such as leaf litter, mid-storey and canopy cover?(4)Does identified predator type vary in terms of number of attacks or attack location on the body of the spider?We used clay models to explore the effects of habitat patch size, microhabitat and seasonal predation on spiders in urban areas. Clay models have been successfully used to assess predation on small taxa such as lizards, snakes, mice, invertebrates and bird eggs28 as birds (33%), lizards (25%), rodents (29%) and wasps (13%).Of the 2400 models used, 663 (28%) were attacked. From marks on the models predators were identifiedLocal predator guilds were defined based on similar predation behaviour across ninety-six model-patch-season units. Six distinct groups were recognised Fig. : group 1Three extrinsic factors fitted using principal component correlation (PCC) were significant using Monte-Carlo attributes in an ordination (MCAO): leaf litter cover and proportion of parkland surrounding the patch within a 150 m and 250 m zone . Overall model accuracy were moderate  with significant variables reported in Table Wasp attacks were found only on spider models (b). Wasps were the only predator that showed significant p < 0.0001) seasonal differences, predating significantly more in summer than in winter  than once by a single identified predator type. However, attack number varied significantly among identified predator types Table . Birds, Bird attack rates were similar for both middle and edges of models Table . Wasps a29.A clear preference for non spider-mimicking controls by all identified predator types indicated that predators were selecting prey based on visual cues, and not only due to curiosity towards foreign objects. The use of controls is surprisingly rare in experiments involving clay models, but is encouraged30 and such guilds may also interact with each other, influencing their impact on prey31. Prey species that are vulnerable to disturbance10 may be further impacted by changes in local predator guilds. Disturbance can also change local predator guilds by disrupting landscape structure and resources that were previously stable32. Generalist predators may be less affected by disturbance than specialists as their broad prey spectrum does not restrict their activities in any particular area33. Amount of parkland surrounding patches significantly influence predator guilds, increasing towards guilds of predominantly rodents and lizards  back to its lair. Records of pompilids collected in Perth  correlate with Aname males roaming phenology (October to February), though they also occur through to April. Wasps may not be targeting specific spider species, but a specific size of prey which may depend on size of the wasp35. For example, C. bicolor may have been attacking large models mistaking them for sparrassids of a similar size, rather than targeting mygalomorphs. Both Aname and some sparrassids, such as Dingosa36, have open burrows for which wasps may display similar searching behaviour. However, spider response varies – Dingosa avoid wasps by running out of their burrow (pers. obs.), whereas mygalomorphs are more likely to defend burrows through phragmosis i.e. defend the burrow using their body. Predation rates on models are limited in this way as they do not reflect actual outcomes of encounters between wasps and prey.Pompilidae, the family of wasps that prey on spiders, is thought to be highly specific to the species or size of spider preyMissulena which has bright red jaws), predation by rodents may be relatively common. Although bats are known to predate on spiders37, their contribution to predation rates is not known and no bat bite impressions were identified in this study. Predators may use senses other than visual cues to locate their prey39. We suggest future predation experiments either test these factors or be mindful when interpreting results.Microhabitat variables and location of predation events indicate that while rodents and lizards predate at similar rates in the same patches, they occupy different microhabitats. Lizards preferred to forage in areas with high leaf litter and canopy cover, while rodents preferred to forage primarily under high understory cover. Location of lizard and rodent bite marks on the edge of control models or on the legs of model spiders probably reflects the approach of these predators at ground-level. Most lizards are active during the day, but rodents are nocturnal. As mygalomorph spiders are thought to roam primarily at night  since Perth was established makes it impossible to know if predation rates are higher, similar or lower than before urbanisation. It is possible that rodents living in native bushland remnants have a similar deleterious effect as they do on islands19. The adaptation of natural predators such as ravens and magpies in urban areas41 may also have a profound impact on spider populations, but potentially only on spiders active during the day (Missulena). High predator mobility, in conjunction with a higher abundance, may be especially detrimental to species restricted to smaller patches14. We found no significant difference in predation type or rate with size of patch, which is worrying, as it suggests that populations in smaller patches may have a higher extinction debt43.As a novel threat, predation by invasive rodents is of high conservation concernTiliqua rugosa), may encounter only a few models during the week, whereas a fast-moving territorial lizard, such as a scrubland skink (Morethia obscura), may encounter many models and multiple times. Site characteristics such as size and microhabitat variables may be accurate indicators for adequate territory ranges for different species. For example, rodents may require a much lower territory range to satisfy their diets than would corvids because of the vast differences in size and mobility capabilities. For future studies, it is advisable that predator range, if known, be taken into account when interpreting results in regards to size and connectivity of patches.It is possible that predation rates by different taxa are not indicative of an individual attacking one model. For example, a raven may learn quickly that models are not suitable food sources after the first instance. Conversely, a wasp may not learn and continue to attack multiple models in the same area indefinitely. As wasps are highly mobile, attacks on multiple spider models over one quadrat may actually indicate low levels of learning, rather than a high density of wasps. Similarly, a slow-moving lizard, such as a bobtail , located in the South-west Australian (SWA) Global Biodiversity hotspoties Fig. .Figure 3To test any effect of season, sampling was conducted during two different time periods in 2016 . Size and phenology replicate real mygalomorph species that occur in the urban remnant vegetation of Perth  , size (mm), location on the model and number of attacks were identified from distinctive marks left by predators on the clay models see Fig. .Figure 5Leaf litter, mid-storey vegetation and canopy vegetation were recorded. We assumed this was related to the visibility of models to predators. Surrounding land-use area was measured by generating shapefile layers of buildings, roads, parkland and other remnant vegetation within 250 m, 150 m and 50 m buffers. Buffers were measured for both patch and quadrats in the open source program Quantum Geographic Information System (QGIS 2014). The Nearmap plugin was used to determine the proportion of different land-use within each buffer area.45, using PATN3.1146. All 2400 models were included in the cluster analysis (predated and non-predated) and converted into a proportion within each unit. Predator types were used as intrinsic factors and combined patch, model type and season were used as separate units (25 models in each unit). The Gower metric was used to determine the degree of similarity between different identified predator types, followed by hierarchical polythetic agglomerative clustering using flexible UPGMA. We used the Two-Step association measure to determine influence of variable groups on identified predator types. A two-way table is a visual representation of the association between different units (guilds) and the influence of identified predator types to form groups. Darker cells show greater association than lighter cells. MDS ordination portrays the spatial relationship between objects in a way that best preserves relative positions. ‘Stress’ measures the level of distortion from reducing axes (to two in this case), with low stress values (i.e. <0.20) indicating better representation of positions than high stress. The Minimal Spanning Tree (MST) is a form of network analysis that connects each object to its nearest neighbours. If there is a high congruence between cluster analysis, ordination and network analysis, then resulting categories are supported. This allows ‘local guilds’32 of predators to be determined and analysis of the influence site variables. Competition within local predator guilds can then also be assessed. During analysis, we found that attack marks from bird species on the clay measuring ≤2 mm and >2 mm birds diverged. Extrinsic factors were fitted to the ordination using PCC and significance determined using MCAO. The strong clustering formed by using patch, model type and season as units indicated that these factors may be useful in predicting identified predator type behaviour through multinomial logistic regression.As this study examines predator behaviour we used predation as intrinsic factors, and determined whether site variables correlated with the resulting multidimensional scaling ordination axes in numerical taxonomic analysis47. Model coefficients (logit) represent the change in log-odds of a variables influence relative to the reference category (in this case “birds”). A positive logit indicates the effect of the predictor on predation (relative to birds) is positive. We have used “b” to represent the logit in results. Predator type  was the response and site, site size, season, model size and type, attack number, attack location and litter, understory and canopy cover the predictors. Data was split into a train and test set  and the packages ‘caret’ and ‘e1071’ used to assess classification accuracy. The package stargazer48 was used to plot significance levels. Predator size categories were reduced for analysis to: 1 (A), 2 (B) and >2 (C). The location of predation was standardised between model type: ‘Body’ of spider models were subsumed into ‘middle’, and spider model ‘legs’ into ‘edge’. The number of attacks was categorised into: 1–4 (A), 5–8 (B) and >8 (C). A multinomial logistic regression was preferred over other GLM’s as several predictors were categorical and the assumptions of normality and homoscedasticity could not be met. Additionally, as model size and type were recorded at the within plot scale and were to be included in the analysis, data was not averaged to predation rate per plot.A MLR was fitted  using predated data only (n = 510). MLR require a nominal dependant variable with more than two levels and can handle categorical variables


Cholangiocarcinoma is a malignant tumor originating from bile duct epithelium. Currently, the treatment strategy is very limited and the prognosis is poor. Recent studies reported celastrol exhibits antigrowth and antimetastasis properties in many tumors. Our study aimed to assess the anti‐CCA effects of cholangiocarcinoma (CCA) and the mechanisms involved in it.In this study, the long‐term and short‐term antiproliferation effects was determined using colony formation and Cell Counting Kit‐8 (CCK‐8) assays, respectively. Flow cytometry was performed to quantify apoptosis. Furthermore, wound healing and transwell assays were performed to determine the cell migration and invasion capabilities, respectively. To further find the mechanism involved in the celastrol‐induced biological functions, LY204002, a PI3K/Akt signaling inhibitor, and an Akt‐1 overexpression plasmid were employed to find whether PI3K/Akt pathway was involved in the celastrol‐induced CCA cell inhibition. Additionally, short interfering RNA (siRNA) was also used to investigate the mechanism involved in the celastrol‐induced PI3K/Akt signaling inhibition. Western blotting and immunofluorescence assays were also performed to detect the degree of relative proteins. Moreover, we validated the antiproliferation and antimetastasis effects of celastrol in vivo by constructing subcutaneous and lung metastasis nude mice models.We discovered that celastrol effectively induced apoptotic cell death and inhibited the capacity of migration and invasion in CCA cells. Further mechanistic study identified that celastrol regulated the PI3K/Akt signaling pathway, and the antitumor efficacy was likely due to the upregulation of PTEN, a negative regulator of PI3K/Akt. Blockage of PTEN abolished the celastrol‐induced PI3K/Akt signaling inhibition. Additionally, in vivo experiments conformed celastrol inhibited the tumor growth and lung metastasis with no serious side effects.Overall, our study elucidated a mechanistic framework for the anti‐CCA effects of celastrol via PTEN/PI3K/Akt pathway. Our research provided mechanistic insight into the anti‐CCA effect of celastrol by the regulation of the PTEN expression, and provide a novel therapeutic strategy for CCA. Mechanically, the blockage of PI3K/Akt ‐mediated signaling by upregulating PTEN is responsible for the changes. Our discoveries provided novel insights into celastrol as a promising anti‐CCA agent.22.1Human cholangiocarcinoma TFK‐1 and HuCCT‐1 cell lines were maintained in RPMI‐1640 medium containing 10% FBS and 1% penicillin‐streptomycin solution  in an incubator with 5% carbon dioxide at 37°C.2.2Celastrol was purchased from Sigma, which was dissolved in dimethyl sulfoxide (DMSO) at the concentration of 100 mmol/L before use. LY294002 was purchased from Abcam Corporation . The cytotoxic activity of celastrol on CCA cells was analyzed using CCK‐8 . Primary antibodies were as followed : cleaved caspase‐3, 9, Bax, Bcl‐2, MMP‐2, 9, vimentin, E‐cadherin, PTEN, PI3K, Akt, p‐Akt, mTOR, p‐mTOR, Ki‐67, NF‐κB. In addition, β‐actin  was used as an internal control.2.3CCK‐8 assay was used to determine the cell viability according to the manufacturer's instructions. Briefly, after cells were seeded in a 96‐well plate and incubated with celastrol for indicated hours. The optical density (OD) values were used as the index of cell viability at the absorbance of 450 nm. Five replicate wells were set up in each group.2.4A total of 700/well cells were firstly seeded in 35‐mm dishes until most of them were attached to the bottom. Then, different concentrations of celastrol was used for each dish. After two weeks, the cells were fixed and stained. Colonies containing ≥ 20 cells were counted.2.5TM C6 flow cytometer (Becton‐Dickinson). Each experiment was conducted for three times.Apoptotic degree of cells was measured by Annexin V‐FITC kit (BD Pharmingen). Cells in each group were firstly digested by trypsin without EDTA. Subsequently, the collected cells were resuspended with binding buffer (500 µL) and annexin V–FITC (5 µL) for 30 minutes. After that, PI (10 µL) was added in dark for 10 minutes at room temperature. Finally, the percentage of apoptotic cells were determined using BD Accuri2.64 cells was initially seeded in each well of a 6‐well plate for 24 hours. Cell layer was scratched by a pipette tip (200 µL). Subsequently, cells were then continued cultured with indicated concentrations of celastrol. Representative wound was imaged by an optical microscope. Each experiment was conducted for three times.A total of 5 × 102.74) were initially suspended with or without celastrol into the upper chamber, and the rest of the steps are the same as our previous reports.The experiment was conducted using 24‐well transwell chambers with 50 µL of Matrigel , and the cell invasive ability is assessed by the number of cells passing through the chambers. Cells  for 20 minutes at room temperature. To increase cell membrane permeability, cells were also incubated with goat serum (10%) and Triton (1%). Subsequently, cells were incubated with antibodies for p‐Akt (Thr308) (1:200), p‐Akt (Ser437) (1:200) or PTEN (1:200) antibodies overnight at 4°C. After that, cells were incubated with an Alexa Fluor‐conjugated IgG secondary antibody  for 1 hour at room temperature. Finally, DAPI was used to locate the nuclei. Each experiment was conducted for three times.2.9Cells were transfected with siRNA‐PTN or scrambled siRNA using Lipofectamine 2000 (Invitrogen). The siRNA sequences were listed as follows: siRNA‐PTEN , and scrambled siRNA . PTEN expression was detected by Western blotting. Akt‐1 plasmid was obtained from GeneCopoeia, Inc. These plasmids and siRNA were subsequently transfected into the cells using the Lipofectamine 2000 reagent (Invitrogen).2.10Proteins expression were evaluated by western blotting as our previous studies described.2.117/0.2 mL PBS) subcutaneously into the right flank for xenograft model. After 2 weeks modeling, mice were randomly divided into 2 groups: celastrol (2 mg/kg) or PBS every 2 days (i.p.). Tumor size was measured every 7 days using calipers. (length × width2)/2 was used to analyzed the volume.BALB/c nude mice  were obtained from Beijing Vital River Laboratory Animal Technology Co, Ltd. All the care and use of animals followed the applicable international guidelines and were approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University. For antiproliferation studies: mice were injected with TFK‐1 cells (1 × 106/0.2 mL PBS) via trail vein. After 2 weeks modeling, mice were randomly divided into two groups: celastrol (2 mg/kg) or PBS every two days (i.p.). All the mice were sacrificed and the lung tissue was harvested after four weeks. All the lung nodules were counted before paraffin embedded.For antimetastasis studies: Mice were injected with TFK‐1 cells , vimentin (1:200), cleaved caspase 3,9 (1:100), PTEN (1:100), and p‐AKT (1:50) were incubated overnight at 4°C. The corresponding secondary antibody was incubated for 1h. Finally, DAB (Invitrogen) was used for color development, and the slides were estimated by three independent pathologists individually.2.14t test or one‐way ANOVA were used for the two groups or more than two groups comparison, respectively. P < .05 was considered statistically significant, and P < .001 was highly considered significant.Statistical analysis was used to elevate all the data. Student's 33.1We initially examined the inhibitory effects of celastrol Figure B,C. To f3.2To examine whether the antiproliferative effect was resulted from apoptosis induction, we performed apoptosis assay. After incubated with celastrol , TFK‐1 and HuCCT‐1 cell lines were analyzed by flow cytometry (FCM) analysis using Annexin V/PI assay kit. Figure Furthermore, western blotting was performed to assessed the important signaling proteins involved in celastrol‐induced cell apoptosis. As shown in Figure 3.3To determine whether celastrol could inhibit migration and invasion of CCA cells, wound healing was initially performed after cultivation with celastrol for 24 hours (a low concentration that did not induce cell apoptosis). According to the data in Figure Epithelial‐to‐mesenchymal transition (EMT) act as a primordial role in cell migration and invasion of cancer cells.3.4Aberrant expression of PI3K/Akt signaling promotes the development of CCA oncogenesis, proliferation, and metastasis.To further elucidate the role of PI3K/Akt pathway in celastrol inhibiting CCA development, we initially pretreated TFK‐1 cells with celastrol at different concentrations , then activated or inactivated the pathway by Akt1 transfection and LY294002, respectively. Cell viability was elevated by CCK‐8 assays. Data showed that overexpression of Akt reverse the celastrol‐induced TFK‐1 cells viability inhibition. Nevertheless, LY294002 treatment resulted in a more inhibition compared to the control groups.  mutations occur in CCA patients, and PTEN acts as a negative regulator of PI3K/AKT signaling pathway in CCA cells. We hypothesized that celastrol elevated PTEN expression, and thus inhibited PI3K/Akt activation. As expected, the PTEN expression was observed significantly upregulated in TFK‐1 cells by western blot, following 24 hours of celastrol treatment Figure A. Additi3.63 followed by treatment of vehicle control or celastrol (2 mg/kg) every 2 days. Figure We initially determined the antiproliferation efficiency of celastrol using a subcutaneous xenograft mice model. 12 mice were initially injected subcutaneously with TFK‐1 cells for 2 weeks, and the tumor volume had reached to a mean size of 115 mmWe subsequently determined the antimetastasis efficiency of celastrol using a lung metastatic mice model. 12 mice were injected with TFK‐1 cells via the trail vein for 2 weeks followed by celastrol treatment. After 4 weeks, the number of nodules and incident rate were drastically decreased with celastrol treatment Figure D compareFurthermore, PI3K/PTEN/Akt signaling‐related proteins expression was analyzed in the excised tumor tissues using Western Blot. As expected, the p‐AKT and vimentin expression were decreased, whereas the cleaved caspase‐9 and PTEN expression were increased according to the data. Figure G A immun4Limited clinical option for treatment remains an aggressive challenge for the patients with CCA, especially in advanced stage. Increasing studies suggest that natural compounds may be a new option for the development of potent cancer treatments.Proapoptosis activity acts as one of the most common antitumor mechanisms to control tumor proliferation, and numerous studies proved that mitochondrial apoptosis plays a vital role in human cholangiocarcinoma.EMT is an important molecular mechanism of invasion and metastasis of malignant tumors.The PI3K/Akt pathway acts as a vital role in tumor oncogenesis and development, including cell viability, autophagy, migration, metastasis, angiogenesis, and drug resistance.PTEN (phosphatase and tensin homologue) is known as a tumor suppressor, which was frequently lost or mutated in various human malignances.5In summary, we report a novel component that exhibits a significant effect on CCA cells growth and metastasis in vivo and in vitro. Further mechanism studies demonstrated that the inhibitory effects are attributed to the induction of apoptosis, and the blockade of migration and invasion might be regulated by perturbations in the PI3K/Akt signaling. Furthermore, and these perturbations were regulated by the drug induce‐PTEN upregulation Figure . TherefoThe authors declare no conflict of interest.Biqiang Zhu designed and performed the experiments. Yunwei Wei analyzed the data. Biqiang Zhu wrote the manuscript.