Case Presentation. Here, we present an interesting case of a patient with SIH who was treated with EBP and developed both immediate RIH after 24 hours and delayed RIH 3 weeks following EBP.  Spontaneous intracranial hypotension (SIH) is a secondary headache that has been attributed to a cerebrospinal fluid (CSF) leak. It may resolve spontaneously or require conservative treatment. An epidural blood patch (EBP) with autologous blood is performed in cases exhibiting an inadequate response to conservative methods. Rebound intracranial hypertension (RIH) can develop following an EBP in up to 27% of patients. It is characterized by a change in the headache features and is often accompanied by nausea, blurred vision, and diplopia. Symptoms commonly begin within the first 36 hours, but could develop over days to weeks. It is important to differentiate this rebound phenomenon from unimproved SIH, as the treatment options differ.  Following EBP for treatment of SIH, new onset of headache having a different pattern and location should always be monitored for the occurrence of RIH. A lumbar puncture should be done if the symptoms of elevated CSF pressure become intolerable or if the diagnosis is uncertain. Lack of early diagnosis and treatment and differentiation from SIH can cause complications and could affect the optic nerves. Spontaneous intracranial hypotension (SIH) is an uncommon but treatable cause of secondary headaches, with an estimated annual incidence of 5 per 100,000 individuals . The mosThere are several noninvasive treatment options for SIH. These include oral hydration, caffeine, theophylline, and bed rest. An epidural blood patch (EBP) with autologous blood is the most common procedure for spinal CSF leaks when conservative methods prove ineffective. It also functions as a diagnostic and therapeutic tool with response rates that vary from 30% to 90% , 6. If tThe most common leak location is the thoracic spine, followed by the cervical spine and less commonly the lumbar spine , 6. WithRebound intracranial hypertension (RIH) has been reported in 7–27.4% of patients after SIH treatment. This complication has been recognized since 1990 , 9. It iHere, we present an interesting case of a patient with SIH treated with EBP who developed both immediate RIH after 24 hours and delayed RIH at 3 weeks following EBP.A 39-year-old female presented with a history of headache over the previous several months, primarily in the occipital area. The headache was exacerbated by sitting or standing and was relieved by lying down. There was no history of trauma nor underlying connective tissue disorder. She had a normal neurologic exam and a BMI of 25.4. The brain MRI demonstrated mild, smooth, diffuse dural enhancement, cerebellar tonsillar herniation at about 6 mm below the level of the foramen magnum, engorged dural sinuses, and a closed pons/midbrain angle, with the corpus callosum splenium depressing the junction of the inferior cerebral vein and vein of Galen .She was diagnosed with SIH, and as the symptoms had not responded to conservative treatment with caffeine and bed rest, she was referred for a blind EBP at the lumbar level. The first patch did not produce an adequate response; thus, a second EBP was done after seven days and relieved the symptoms. After several months, she was referred to our center with sudden-onset low back pain radiating to the neck and occipital area. The headache persisted in an orthostatic pattern and was accompanied by nausea and dizziness. She was admitted for further evaluation, and the physical examination revealed no systemic or neurologic deficits. A panspinal MRI was performed which revealed a fluid signal intensity area posterior to the ligamentum flavum at the C2 level without any definite evidence of a defect in the ligamentum flavum. There was no evidence of dural leakage in thoracic region.Because of the inadequate response to conservative care comprising hydration, bed rest, and caffeine, the patient underwent another EBP. The patch was performed by an expert anesthesiologist with an 18-gauge needle at the L2 and L3 levels using 15 cc of her own blood. The patient maintained a 30-degree Trendelenburg position for 6 hours after the procedure. She experienced immediate relief of the orthostatic headache, but her headache pattern changed by 24 hours following the procedure. It was mostly felt in the frontal area and was improved by sitting, but was aggravated by lying down. Her neurologic examination was normal, and she was diagnosed with early RIH. The headache was relieved after two days of conservative management, and she was discharged from the hospital in good condition.2O with normal CSF analysis which confirmed the diagnosis of delayed RIH. She was treated with head elevation and intravenous mannitol, followed by oral acetazolamide, which was titrated up to 500 mg three times a day. The lumbar puncture was repeated after six days, and the CSF pressure was 38 cm H2O. Quantitative perimetry showed enlargement of the blind spot, and OCT demonstrated perineural fluid accumulation, but both resolved following treatment for two weeks with acetazolamide. The headache improved within three to four months, and the administration of acetazolamide was tapered-off and discontinued after this period with no recurrence of symptoms.The patient returned to the hospital after two weeks because of recurrence of the positional headache accompanied by diplopia and blurred vision. The neurologic exam revealed bilateral sixth nerve palsy and swollen optic discs with hemorrhage. The patient was admitted again for neuroimaging and to measure the CSF pressure. The brain MRI and venography showed no abnormalities, and a lumbar puncture was done. The opening CSF pressure was 50 cm HSpontaneous intracranial hypotension can resolve either spontaneously or with conservative treatment that includes bed rest, oral hydration, and caffeine intake. For patients who do not adequately respond to a conservative approach, injection of autologous blood into the spinal epidural space is the preferred invasive treatment. The success rate for each EBP varies from 30% to 70% for nontargeted patching and up to 87% for targeted patching , 5, 6, 9The first EBP has been reported to have shown successful clinical improvement in 64% of patients without the need for further intervention. However, a single EBP may not produce a permanent response in some patients, and one or two additional patches at least seven days apart may be required to produce complete relief of symptoms , 10, 11.RIH is an infrequently reported complication of EBP in patients with SIH. It results from postprocedural elevation of the CSF pressure. Up to 27% of patients can develop intracranial hypertension following a blood patch for treatment of SIH , 6, 13.The Monro–Kellie hypothesis asserts that the total volume within the skull is constant and volume loss in one compartment will be compensated for by an increase in the other compartments. These compensatory mechanisms in SIH can lead to subdural fluid collection, venous system engorgement, and a possible increase in CSF production. Early RIH that occurs immediately after EBP can be explained by the failure of intracranial venous distension to reverse immediately after repair of the CSF leak. Delayed RIH can develop days to weeks after EBP. The proposed mechanisms for this include upregulation of CSF production and disrupted CSF reabsorption during the period of the CSF leak , 14–17.2O, which was immediately treated with head elevation and intravenous mannitol, followed by oral acetazolamide for three to four months.Our report is an interesting case of a patient with SIH treated with EBP who developed both early RIH after 24 hours and delayed RIH at three weeks post-EBP. A failure to correctly diagnose RIH and its differentiation from SIH can cause complications for a patient because the treatments are different. For a rebound headache, the strategy for management is to lower the CSF pressure [2O (range of 22–55), and all cases improved following lumbar puncture and administration of acetazolamide for durations varying from five days to three years. In most RIH cases reported, the onset of symptoms has been rapid (from immediate to three days) and papilledema has been rarely reported, possibly due to the appearance of the usual fundoscopic changes over a period of days to weeks. The CSF opening pressure measurement in these patients ranged from 20 to 55 cm H2O [Kranz et al.  reported5 cm H2O , 18, 19.2O) [There are few reports of delayed RIH in the literature. In a study of 113 patients with SIH who underwent percutaneous or microsurgical treatment, 27.4% of patients developed RIH. In 23 patients, it occurred within 72 hours, in seven patients in 3–7 days, and in two patients in 7–30 days. Funduscopic examination showed papilledema in only two patients. A lumbar puncture was performed in four patients and found elevated pressure in only one patient (30 cm H2O) .CSF pressure is measured infrequently in RIH because of the increased likelihood of postdural puncture headache. Therefore, the diagnosis of rebound intracranial hypertension primarily has been clinical. Lumbar puncture is done when the symptoms of elevated CSF pressure become intolerable, if visual perception problems develop, or if there is doubt about the diagnosis of rebound high-pressure headache.2O.Our patient developed both types of rebound headache after EBP. The location of the headache changed from the occipital to frontal areas, and the orthostatic feature reversed. The early positional headache was relieved after two days, whereas the delayed one did not respond to conservative management and a lumbar puncture was done after the symptoms and signs of increased intracranial pressure appeared. The opening CSF pressures recorded at the different times were 50 and 38 cm HAs in cases like that reported by Kranz et al. , our patThe discovery of previously elevated CSF pressure in 3% of patients with SIH, as well as the appearance of intracranial hypertension following surgical closure of the CSF leak in some reports, suggest that increased pressure could predispose a patient for a CSF leak at a weak point in the dura. This would be especially true for patients who develop delayed RIH after EBP . Our pat


Surface electromyography (sEMG) is vulnerable to environmental interference, low recognition rate and poor stability. Electrocardiogram (ECG) signals with rich information were introduced into sEMG to improve the recognition rate of fatigue assessment in the process of rehabilitation.Twenty subjects performed 150 min of Pilates rehabilitation exercise. Twenty subjects performed 150 min of Pilates rehabilitation exercise. ECG and sEMG signals were collected at the same time. Aftering necessary preprocessing, the classification model of improved particle swarm optimization support vector machine base on sEMG and ECG data fusion was established to identify three different fatigue states . The model effects of different classification algorithms  and different fused data types were compared.IPSO-SVM had obvious advantages in the classification effect of sEMG and ECG signals, the average recognition rate was 87.83%. The recognition rates of sEMG and ECG fusion feature classification models were 94.25%, 92.25%, 94.25%. The recognition accuracy and model performance was significantly improved.The sEMG and ECG signal after feature fusion form a complementary mechanism. At the same time, IPOS-SVM can accurately detect the fatigue state in the process of Pilates rehabilitation. On the same model, the recognition effect of fusion of sEMG and ECG is better than that of only using sEMG signal or ECGsignal. This study establishes technical support for establishing relevant man–machine devices and improving the safety of Pilates rehabilitation. Pilates is a combination of strength, flexibility, and balance exercises. It focuses on lumbopelvic stabilization, with the activation of the deep muscles of the trunk, and seeks a complete connection of body and mind . The corCommon detection techniques for muscle fatigue include surface electromyography (sEMG) , muscle Compare with EEG, Electrocardiogram (ECG) is one of the most commonly used non-invasive diagnostic tools for recording the physiological activities of the heart over some time. The ECG data  containsConsidering the muscle fatigue characteristics of the sEMG and ECG, it is of great significance to establish the fatigue state recognition model of the Pilates rehabilitation process by the fusion sEMG and ECG . Data fuThe fatigue degree of the subjects after the Pilates rehabilitation was divided into 6–20 score ranges by the scale for Rating of Perceived Exertion  . The segIn this section, the data collection will be described, and analysis methods will be explained in detail. The data has been obtained from 20 physical health subjects .The experiments were conducted using Trigno Wireless Systems and Smart Sensors. The Trigno Wireless EMG system is a very popular device with simple and reliable performance. Each EMG sensor has a built-in triaxial accelerometer. Its signal can be transmitted in 40 m and can be detected continuously for 8 h. The system can transmit the data stream to EMGworks 4. Acquisition and analysis software for generating 16 EMG sensors (37 mm × 26 mm × 15 mm) and 48 accelerometer analog channels for integration with motion capture and other third-party data acquisition systems. The complete trigger function further expands the possibility of integration with other measurement technologies. The sensor used can respond immediately to the interference detected on the skin surface.The North Sichuan Medical College conducted this research project by the ethical code of the World Medical Association. It was also approved by the Ethics Committee of the North Sichuan Medical College (No. 2020ER(R)017). This paper took 20 physical examiners as the research object. Selection criteria: full-time students majoring in Physical Education; aerobics as the main special sport; the subjects were in good physical condition, had no obvious disease, and had no damage to the lower limb muscles and knees. The subjects had an average height of 162.3 ± 1.2 cm, an average body weight of 63.5 ± 2.3 kg, and an age of 21.2 ± 1.1 years. Before the experiment, the experimental process was explained to the subjects. All subjects voluntarily participated in the experiment and signed written informed consent. The test time was September 11–25, 2021.According to the physiological structure of the human body, the ECG signal and the sEMG signal at the anterior tibialis muscle and semitendinosus muscle were collected synchronously. The sampling frequency was 2 kHz. The sensor position is shown in Fig. The subjects were divided into two groups of 10. The prescribed Pilates movement training was carried out according to the plan. It was stipulated that 15 min was a training cycle. Ten subjects completed one cycle of training in turn as a group of experiments. The duration of each experiment was 150 min, and a total of 40 groups of experiments were carried out. The first group finished the test, the second group continued the test, and the first group rested. In each training cycle, the subjects return a calm standing state every 30 s according to the RPE scale , report The sEMG and ECG signal in three states were marked and saved, and the corresponding training time was recorded. 30 groups of sEMG and ECG signal were obtained in each group experiment. According to the corresponding fatigue value, each data was divided into three states, with a total of 90 sEMG and ECG data. After the experiment, 3600 sEMG and ECG data were collected respectively. One set of experimental processes and obtained characteristic data are shown in Fig. The original sEMG and ECG signal contains noise interference, which needs to be preprocessed. Firstly, the original ECG and sEMG signals were filtered by 0–100 Hz and 0–500 Hz low-pass filters to remove high-frequency interference. Secondly, 49.5–50 Hz adaptive notch filters were used to filter the power frequency and harmonic interference in the signal. Finally, empirical mode decomposition(EMD) and discrete wavelet transform(DWT) domains were used to reduce the noise . which rThe calculation method of specific parameters with an asterisk in the Table RRi is the duration of ECG interval; M is the total number of periods.x(t) is the amplitude of the sEMG signal, x(k) is the amplitude of sEMG signal after discretization, Fs is sampling frequency. N, N1, and N2 are the length of sEMG signal, P(f) is the power spectral density function [In the above relations, function .Traditional feature fusion with constant weights attempts to merge multiple feature vectors into a vector, which performs poorly in muscle fatigue recognition since feature weights cannot change with the testing object . In thisa,b are the vector dimension and n is the number of samples. d, X can be divided into the training set Xp and the test set XT. Xp is used for training the classifier and XT is used for validating the classification performance.SVM, as a kind of machine learning method based on statistics and the principle of structural risk minimization, performs excellently in addressing nonlinear recognition problems with a small set of samples . FatigueXp contains m samples, yi can be classified into the following 3 states—relaxed state, transition state, and tired state, with the values of − 1, 0 and 1, respectively. SVM attempts to seek an optimal classification function so that the distance of the function on the hyperplane and the support vector reaches the maximum. The kernel function φ(x) is used for mapping the sample set to high-dimensional space while satisfying the Mercer condition. The selection of φ(x) can directly determine the classification performance. Owing to favorable performance and application range, radial basis function is selected as the kernel function of SVM in this study,It is assumed that the training set φ, the problem of seeking optimal hyperplane can be converted into the following convex quadratic programming problem:a, the convex quadratic programming problem can be converted into the dual problem according to Eq. .Training of SVM network and calculation of the particle fitness degree. The characteristic samples are fused with the corresponding fusion coefficients of particles to obtain the feature fusion matrix D). For the fitness degree h(d) of each group of particles after the above step b, the optimal fitness degrees of both individual particle and population are calculated according to Eq. , where D denotes the optimal fusion coefficient matrix.Step b and Step c are repeated until reaching the optimal fitness degree  are selected from the collected data for pre-processing and feature extraction; next, the established IPSO-SVM classifier is trained and tested via Monte Carlo cross-validation (MCCV). Figure The fusion coefficient is the key to establishing the optimal feature vector and enhancing the fatigue recognition rate. To prevent from falling into local optimum of particle fitness degree, the related parameters in PSO including the population size Some commonly-used classification methods for physiological signals including IPOS-SVM, BP neural network (BPNN), K-nearest neighbor (KNN), and linear discriminant analysis (LDA) were performed on sEMG and ECG signals for training and testing, as the results are shown in Fig. Aiming at exploring the enhancement of classification performance via data fusion, the classification models are constructed on sEMG signal, ECG signal and the combination of two signals based on IPOS-SVM, as the results are shown in Fig. The recognition rates of relaxed, transition and tired states only with sEMG signal were 94.00%, 87.75% and 89.5%, respectively, while the recognition rates of relaxed, transition and tired states only with ECG signal were 88.5%, 80.00% and 87.25%, respectively. By contrast, sEMG was more sensitive to fatigue state and rich in fatigue state information. ECG showed a poorly recognition rate of the transition state (only 80%). After feature fusion of sEMG and ECG, the recognition rates of the relaxed state, the transition state and the tired state could be remarkably enhanced to 94.25%, 92.25% and 94.25%, respectively. The recognition rate of transition rate exceeded 90%, which can be explained by the following two reasons. Firstly, ECG features can contribute to recognizing interference variables and play the role of correction. Secondly, IPOS-SVM can perform distribution based on the trust degrees of high-dimensional characteristics after multiple iterative computations, which can assign appropriate weights in different cases.The fatigue produced in Pilates is a complex phenomenon in rehabilitation exercises. How to enhance the accuracy of fatigue estimation based on feature fusion of multi-source physiological signals appears as an effective mean. However, due to the lack of uniform research paradigm and standards, many studies have been stuck on laboratory or special application scenarios. Both sEMG and ECG are nondestructive body monitoring signals abundant in physical information. Establishing the classification model or quantitative model based on the combination of sEMG and ECG shows huge potential. This study starts from the perspective of fatigue in Pilates and proposes a lower limb fatigue estimation method based on sEMG and ECG to achieve the classification of 3 states  in the lower limb rehabilitation process. The classification model by integrating ECG and sEMG fatigue features into fatigue states is established with IPOS-SVM. Results also confirm better classification performances of IPSO-SVM than BPNN, KNN and LDA, i.e., the proposed IPSO-SWM is appropriate for the classification of fatigue states based on sEMG and ECG signals. IPSO-SVM classification model based on surface electromyography and ECG fusion features had good processing ability for high-dimensional feature information, and can well identify 3 fatigue states with the recognition rates of 94.25%, 92.25% and 94.25%, respectively. The mean recognition rate was 93.58%. Compared with the study report of Shangbin Li  (ReconitIt must be admitted that there are deficiencies in this study. IPSO-SVM in the paper pays more attention to enhancing the recognition rates of different fatigue states. Compared with single detection means, the operability of operators and the complexity should be further optimized. Meanwhile, this study focused on the recognition of 3 discrete states during the rehabilitation process. In future studies, our team will attempt to explore the mapping relations between continuous fatigue states and ECG/sEMG signals to establish a more accurate quantitative model of muscle state.


Pseudomonas aeruginosa (PA) are a therapeutic challenge. Data demonstrating the pharmacokinetic/pharmacodynamic (PK/PD) properties of newer beta-lactamase inhibitors remains scarce. A clinical challenge lies in selecting an antimicrobial regimen that diffuses across the blood brain barrier and maintains concentrations to achieve PD targets associated with bacterial killing. These complexities compelled us to quantify the pharmacological properties of ceftazidime/avibactam (CZA). Utilizing therapeutic drug monitoring (TDM), we evaluated the adequacy of therapy and aimed to guide precise CNS dosing in the treatment of three patients with neurosurgical meningitis.Central nervous system (CNS) infections caused by carbapenem-resistant Enterobacterales (CRE) and Difficult-to-treat resistant (DTR)-Bacterial identification and susceptibility testing were performed using MicroScan. TDM of CZA was implemented using a dose of 2.5 g infused intravenously over 2-hours, every 8 hours. The concentrations of ceftazidime and avibactam were determined by liquid chromatography/mass spectrometry. For patients 2 and 3, four unique CSF and plasma samples spanning the dosing interval were obtained; including trough values. (See table)blaKPCKp (0.25μg/mL), DTR PA (4 μg/mL), and blaKPCE. cloacae (0.25 μg/mL), respectively. Measured plasma and CSF concentrations of avibactam (AVI) and ceftazidime (CAZ) are shown in Table 1.Bacterial identification and CZA MICs for patients 1, 2, and 3 revealed Table 1a. Therapeutic Drug Monitoring of CAZ-AVI depicting dosing, time of samples, and measured concentrations in CSF and Human Plasma (HP)Table 1b. Therapeutic Drug Monitoring of CAZ-AVI concentrations in CSF and Human Plasma (HP) pertaining to patient 2 and 3Measuring CZA concentration levels in CSF was achieved in 3 patients with complicated CNS infections. Post-infusion concentrations indicated that adequate CAZ and AVI exposures were attained in the CSF. Notably, avibactam was shown to achieve concentrations ≥1 µg/ml in the CSF throughout the dosing interval. For avibactam and ceftazidime, the PK/PD target correlated with bacterial killing is ~50% fT >MIC. In 2 out of 3 patients, concentrations were determined to be above the respective MICs throughout the entire dosing interval in the CSF. All patients attained clinical and microbiological cure. A novel CZA TDM method was successfully employed to establish that CZA maintains therapeutic CSF concentrations that exceed the MIC throughout the dosing interval. Robert A. Bonomo, MD, entasis (Research Grant or Support)Merck (Grant/Research Support)NIH (Grant/Research Support)VA Merit Award (Grant/Research Support)VenatoRx (Grant/Research Support)


Abnormal spindle-like microcephaly-associated (ASPM) gene encodes a spindle protein that is commonly implicated in primary microcephaly. We found that ASPM is recruited to sites of DNA damage in a PARP2-dependent manner. ASPM interacts with BRCA1 and its E3 ligase HERC2, preventing HERC2 from accessing to BRCA1 and ensuring BRCA1 stability. Inhibition of ASPM expression promotes HERC2-mediated BRCA1 degradation, compromises HR repair efficiency and chromosome stability, and sensitizes cancer cells to ionizing radiation. Moreover, we observed a synergistic effect between ASPM and PARP inhibition in killing cancer cells. This research has uncovered a novel function for ASPM in facilitating HR-mediated repair of DSBs by ensuring BRCA1 stability. ASPM might constitute a promising target for synthetic lethality-based cancer therapy.DNA double-strand break (DSB) repair by homologous recombination (HR) is essential for ensuring genome stability.   •ASPM is recruited to sites of DNA damage in a PARP2-dependent manner.•ASPM promotes DSB-end resection to facilitate HR repair.•ASPM prevents HERC2 from accessing to BRCA1 and ensuring BRCA1 stability.•Inhibition of ASPM sensitizes cancer cells to ionizing radiation and PARP inhibitor. Molecular biology; Cell biology; Functional aspects of cell biology MCPH can result from mutations in at least 25 genes, while mutations in the PM) gene  are the PM) gene . We are PM) gene , 2006; (PM) gene ; (3) MCPPM) gene .Brca1 knockout mice helped demonstrate that Brca1 is required for embryonic neurodevelopment by preventing Atm/p53-dependent apoptosis of early neural progenitors  HeLa cells by CRISP-Cas9 technology. Specifically, we knocked in an FLAG-GFP tag prior to the art site A. Genotyart site B. FLAG-Gart site C and S1Dart site E. FLAG-Gart site F. Again,art site F. ASPM iWe then mapped the region(s) essential for ASPM recruitment to UV laser-induced DNA damage stripes. We generated GFP-tagged expression constructs for full length ASPM (GFP-ASPM), isoform 2 of ASPM with exon 18 skipping (GFP-ASPM2), and various truncation mutants G. GFP-ASHaving shown ASPM enrichment onto DSBs, we next sought to determine if ASPM is involved in DSB repair. We inhibited ASPM expression using three-independent siRNA oligos transfected into HR-mediated repair reporter system DR-U2OS cells, the micro-homology end-joining (MMEJ) reporter system MMEJ-U2OS cells, and non-homologous end-joining (NHEJ) reporter system EJ5-U2OS cells, respectively. Reducing ASPM expression compromised HR-mediated DSB repair A but notASPM knockout (KO) HeLa cells, targeting exon 4 by CRISPR-Cas9 technology. We identified one clone with a premature stop codon after Phe691  domain (for DNA binding) at its N terminus for binding to DNA, while PARP2 has one WDR domain but lacks the zinc fingers and BRCT domain . These dAspm genetically interacts Wdr62  to control brain size and direct WDR62 localization, and both proteins help localize CENPJ/MCPH6 to the centrosome  9.5 demonstrated that Brca1 is required for the cerebral cortex to develop to normal size by preventing the apoptosis of early cortical progenitors  supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin .Human U2OS cells, DR-U2OS cells (for HR) expressing an HR-mediated DSB repair reporter system , EJ5-U2OAll ASPM fragments were sub-cloned into a pEGFP-C1 vector. Olaparib (S1060), Etoposide (S1225), MG132 (S2619), Cycloheximide (S7418), NU6027 (S7114), KU55933 (S1092) and NU7026 (S2893) were purchased from Selleck. Rabbit anti-ASPM(BL1615), anti-RPA32 (A300-244A), anti-pKAP1 S824 (A700-013), anti-KAP1 (A700-014), anti-BRCA1 (A301-377A), anti-pRPA32 S33 (A300-246A) and anti-ATM (A300-299A) antibodies were purchased from Bethyl. Rabbit anti-pATM S1981 (ab81292) and anti-HERC2 (ab85832) were purchased from Abcam. Anti-BRCA1 (sc-6954) and anti-CtIP (sc-271339) was purchased from Santa Cruz, anti-BrdU (347580) from BD Biosciences, and anti-FLAG M2 (F1804), anti-FLAG® M2 Affinity Gel (A2220) and anti-β-actin (A5441) from Sigma.ASPM knock out (KO) cell lines were generated by CRISPR-Cas9  genome editing technology. The resulting cell lines were designated as FLAG-GFP-ASPM KI and ASPM KO, respectively. For ASPM KO, an ASPM-specific single-guide RNA (sgASPM: GACTGTGCCACAGCGATAAT) was inserted into the pSpCas9(BB)-2A-Puro vector (PX459) . HeLa cells were transfected with PX549 (sgASPM) to introduce a single double-strand break (DSB) within the ASPM exon 4. The transfectants were treated with puromycin (1 μg/mL) for 2 days; then, re-seeded cells with different dilution factors were left to grow for a further 15 days before the identification and recovery of single-cell colonies. For FLAG-GFP-ASPM KI, a single-guide RNA (sgRNA: TCGAATCTGCCATGGCGAAC) was inserted into pSpCas9(BB)-2A-GFP (PX458) . Gibson Assembly was used to assemble pDsRed N1 vector-based FLAG-GFP donor plasmids . HeLa cells were co-transfected with PX458 (sgASPM) and RFP-FLAG-GFP donor plasmids to introduce a DSB before ASPM exon 1. Both GFP- and RFP-positive single cells were selected by flow cytometry 2 days after transfection. Single clones were further confirmed by PCR and sequencing for the correct product flanking FLAG-GFP within the ASPM locus, immunofluorescence  and immunoprecipitation .Both FLAG-GFP in-frame knock in (KI) and U2OS and HeLa cells were grown on a glass bottom cell culture dish  and then irradiated with a 365 nm UV laser  generated from a Micropoint System (Andor). Images were captured every 10 sec under a DragonFly confocal imaging system (Andor). The fluorescence images were analyzed using ImageJ (NIH). For ionizing radiation (IR), HeLa cells were exposed to 1.6 Gy/min generated by a Radsource RS-2000pro X-Ray irradiator.The following siRNA oligonucleotide duplexes were used: ASPM 1# (5’ GUGGUGAAGGUGACCUUUCdTdT3’); ASPM 2# (5’AUGCUAACAAGCAGGUUAAUU-dTdT-3’); ASPM 3# (5’CACUCGUCAUUCAGAAAUAdTdT-3’); HERC2 (5’ GCGGAAGCCUCAUUAGAAAdTdT-3’), BRCA1 ( 5’ CUAGAAAUCUGUUGCUAUGdTdT-3’) , RIF1 (5’-AGACGGUGCUCUAUUGUUAdTdT-3’), CtIP (5’ GCUAAAACAGGAACGAAUCdTdT-3’), PARP1 (5’-CAAAGUAUCCCAAGA AGUUdTdT-3’); PARP2 (5’-CUAUCUGAUUCAGCUAUUAdTdT-3’). All siRNAs were transfected into cells using Lipofectamine™ RNAiMAX .Total RNA was extracted using an RNA isolating Kit (Foregene) according to the manufacturer’s instructions. Then, 1 μg total RNA was used for cDNA synthesis with random hexamers. The following primers were used in the RT-PCR amplification: PARP1-F: CGGAGTCTTCGGATAAGCTCT, PARP1-R: TTTCCATCAAACATGGGCGAC, PARP2-F: GCCTTGCTGTTAAAGGGCAAA, PARP2-R: TCCTTCACAATACACATGAGCC, ASPM-F: TGCAGTGGGTGAACATGAAAA, ASPM-R: CGAAGAGGGTGTTACCTCGTTT, BRCA1-F: TTGTTACAAATCACC CCTCAAGG, BRCA1-R: CCCTGATACTTTTCTGGATGCC. For the initial amplification, the PCR proceeded with a denaturation step at 95°C for 10 min, followed by 28 cycles of denaturation at 95°C for 1 min, primer annealing at 55°C for 30 s, and primer extension at 72°C for 45 s, before a final extension at 72°C for 5 min. Real-time PCR was carried out using an ABI PRISM 7500 Sequence Detection System (Applied Biosystems). The housekeeping gene β-actin  was used as an internal control.Immunoblotting and immunoprecipitation were performed as previously described .For immunofluorescence, U2OS and HeLa cells were first micro-irradiated with a MicroPoint System (Andor) or exposed to IR as described above. Both cell types were washed with PBS and then fixed with 4% paraformaldehyde (PFA) at room temperature (RT) for 5 min, permeabilized with Triton-X100 (0.5%) for 5 min, and blocked with 2% BSA (in 0.1% PBST) for 30 min at RT. The cells were incubated with primary antibody for 1 h, and then washed three times with PBST before being incubated with a fluorescent-conjugated secondary antibody for a further 1 h. The cells were then stained with DAPI for 2 min and images were captured using a DragonFly confocal imaging system (Andor).For BrdU incorporation (ssDNA staining), HeLa ASPM KO or knock down cells were cultured with BrdU (10 μM) for 24 h. The cells were then exposed to 10 Gy IR and then permeabilized with Triton-X100 (0.5%) for 3 min, fixed with 4% PFA for 10 min and blocked with 2% BSA (in 0.1% PBST) for 30 min all at RT. After washing with PBS, the cells were incubated with an anti-BrdU antibody for 1 h followed by three washes with blocking buffer before a FITC-conjugated secondary antibody was added and incubated for 1 h. For EdU labeling (S/G2 phase), HeLa ASPM KO or knock down cells were cultured with EdU (10 μM) for 2 h and then exposed to 10 Gy IR. After 6 h, the cells were treated according to the procedure described in the YF®647A Click-iT EdU Imaging Kit .DR-U2OS (HR) and EJ5-U2OS (NHEJ) cells, containing a single copy of a DR-GFP or EJ5-GFP reporter gene (respectively) integrated into the genome were used for DSB repair assays. The assays were performed as previously described . MMEJ-GFMetaphase chromosome analysis was performed as previously described . BrieflyASPM KO or knock down HeLa cells were split into 6-well plates at a density of 150 cells per well. The cells were exposed to 0, 1, 2, 4 Gy IR or 0, 0.25, 1, 5 mM Olaparib and then incubated for 14 days. The surviving colonies were fixed and stained with crystal violet.All experiments were repeated three times independently. All statistical analyses were performed in Microsoft Excel and GraphPad Prism 8. A two-tailed non-paired Student’s t-test was used to determine significant differences between two treatment groups. A p value <0.05 was considered statistically significant. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001; ns, not significant.


There is limited evidence on the use of high-sensitivity C-reactive protein (hsCRP) as a biomarker for selecting patients for advanced cardiovascular (CV) therapies in the modern era. The prognostic value of mildly elevated hsCRP beyond troponin in a large real-world cohort of unselected patients presenting with suspected acute coronary syndrome (ACS) is unknown. We evaluated whether a mildly elevated hsCRP (up to 15 mg/L) was associated with mortality risk, beyond troponin level, in patients with suspected ACS.We conducted a retrospective cohort study based on the National Institute for Health Research Health Informatics Collaborative data of 257,948 patients with suspected ACS who had a troponin measured at 5 cardiac centres in the United Kingdom between 2010 and 2017. Patients were divided into 4 hsCRP groups . The main outcome measure was mortality within 3 years of index presentation. The association between hsCRP levels and all-cause mortality was assessed using multivariable Cox regression analysis adjusted for age, sex, haemoglobin, white cell count (WCC), platelet count, creatinine, and troponin.n = 38,390), 2 to 4.9 mg/L , 5 to 9.9 mg/L , and 10 to 15 mg/L ). On multivariable Cox regression analysis, there was a positive and graded relationship between hsCRP level and mortality at baseline, which remained at 3 years (hazard ratio (HR) (95% CI) of 1.32 (1.18 to 1.48) for those with hsCRP 2.0 to 4.9 mg/L and 1.40 (1.26 to 1.57) and 2.00 (1.75 to 2.28) for those with hsCRP 5 to 9.9 mg/L and 10 to 15 mg/L, respectively. This relationship was independent of troponin in all suspected ACS patients and was further verified in those who were confirmed to have an ACS diagnosis by clinical coding. The main limitation of our study is that we did not have data on underlying cause of death; however, the exclusion of those with abnormal WCC or hsCRP levels >15 mg/L makes it unlikely that sepsis was a major contributor.Following the exclusion criteria, there were 102,337 patients included in the analysis  may be a clinically meaningful prognostic marker beyond troponin and point to its potential utility in selecting patients for novel treatments targeting inflammation.NCT03507309ClinicalTrials.gov -  Amit Kaura and colleagues investigate whether mildly elevated high sensitivity C-reactive protein is associated with mortality risk in patients with suspected acute coronary syndromes. C-reactive protein (CRP) is a protein produced by the liver and released into the bloodstream in response to inflammation. A blood test called a high-sensitivity C-reactive protein (hsCRP) accurately measures low levels of CRP.In patients presenting with a suspected heart attack, low levels of hsCRP on admission may prove useful in predicting death beyond using troponin, a marker of heart muscle damage.In this study of 102,337 patients with suspected heart attack, a higher hsCRP level was associated with a higher risk of death.This relationship was independent of the troponin level in all patients with suspected heart attack and was further verified in those who were confirmed to have a heart attack.These findings suggest that hsCRP is a clinically meaningful marker of risk of death in addition to troponin in patients with suspected heart attack.hsCRP has potential utility in selecting patients with heart attack for new treatments that target reducing inflammation. Inflammation has been extensively studied and postulated as mechanistic in atherothrombosis . Much deIn early observational studies of general and acute coronary syndrome (ACS) populations, high levels of CRP were found to represent a poorer prognosis, perhaps underlying a previously unrecognised inflammatory process relating to atherosclerosis ,4–6. FurConsidering high-sensitivity C-reactive protein (hsCRP) levels in a stable populations as a biomarker for selecting patients for advanced CV therapies in the modern era was pioneered by the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS), a randomised, double-blind, placebo-controlled trial of canakinumab , in preventing recurrent CV events. Patients in the canakinumab arm had a significant 15% reduction in CVD events over median 3.7 years of follow up, coexistent with reduced hsCRP levels and independent of lipid lowering .Results of the Cardiovascular Inflammation Reduction Trial (CIRT) had shed some doubt onto the role of modulating inflammation in atherosclerosis using rheumatological agents, after it terminated early and reported that low-dose methotrexate had no effect on CVD versus placebo . HoweverHowever, in patients presenting with suspected ACS, levels of hsCRP may either reflect background atherosclerotic disease activity or indeed also reflect the sequelae of the acute event. Nevertheless, hsCRP levels at presentation may prove useful in prognostication beyond routinely studied parameters, including troponin.In this study, we aim to evaluate the prognostic value of mildly elevated hsCRP (up to 15 mg/L) beyond troponin in a large real-world cohort of unselected patients presenting with suspected ACS. Our hypothesis was that a mildly elevated hsCRP would be associated with mortality risk, beyond troponin, in patients with suspected ACS.ClinicalTrials.gov, NCT03507309.We conducted a retrospective cohort study based on the National Institute for Health Research Health Informatics Collaborative data –22 of 25We developed a data model to capture the longitudinal record for patients with a suspected ACS, characterised by the request of a troponin test. For patients with multiple episodes of care for which troponin was tested, the first episode of care was used. We intentionally focused our population to those with normal white cell count (WCC) in an attempt to exclude overtly septic patients or those with haematological disorders that may have a major effect on levels of hsCRP. Furthermore, we excluded all patients with hsCRP >15 mg/L in a separate effort to exclude those with clinically significant inflammation or infection. All eligible patients were followed up, using routinely collected data on the National Health Service (NHS) Spine Application, until death or censoring in April 2017.All analyses on hsCRP and other haematological and biochemical blood tests, apart from troponin, were performed using the first result measured during the hospital care episode.The 99th percentile of the upper limit of normal (ULN) and the limit of detection of all hsCRP assays used across all cardiac centres were determined.All analyses on troponin were performed using the peak troponin level. For patients who had a single troponin measurement, the peak troponin was based on this measurement. In the remainder of the patients who had more than one troponin test in the same hospital episode of care, the peak troponin value was defined as the highest of all measurements. We standardised the different troponin assays between the academic centres by scaling the results using the ratio of the observed troponin value divided by the ULN for each troponin assay. Each centre measured troponin I or troponin T using either contemporary or high-sensitivity assays . These tPatients who were admitted to the hospital had the International Classification of Diseases (ICD) discharge codes. Patients were classified as ACS based on the assigned ICD-10 codes  25]..25].The population was divided into 4 categories, those with a normal hsCRP (<2 mg/L)  and 3 grThis study was approved by the London South East Research Ethics Committee (REC reference: 16/HRA/3327). This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline .2 test for trend for continuous and categorical variables, respectively. The correlation between hsCRP and troponin concentrations was assessed using the Spearman correlation coefficient. The Kaplan–Meier method was used to calculate and display cumulative mortality, with hsCRP groups compared using the log-rank statistic. Subgroup analyses were performed for troponin positivity and ACS diagnosis.Descriptive statistics are displayed as median (interquartile range (IQR)) for continuous variables and number (%) for categorical variables. Comparisons between hsCRP groups with regard to baseline characteristics were explored using Kruskal–Wallis 1-way analysis of variance test and χMultivariable Cox regression analysis was applied to investigate whether the baseline hsCRP groups independently predict 3-year mortality after adjusting for other demographic and clinical variables. The proportional hazard assumption was violated with a significant relationship between the Schoenfield residuals of all covariates and time. Cox regression analysis with time-varying coefficients was therefore used with follow-up time divided into 6 intervals: <1 month, 1 to 3 months, 3 to 6 months, 6 to 12 months, 12 to 24 months, and 24 to 36 months. The proportional hazard assumption was met in each of these time intervals. The coefficients calculated during each of these time intervals were based on the variables measured during the index hospital admission. Furthermore, using Martingale residuals, nonlinearity was detected in the relationship between the log hazard and all continuous covariates. To model these nonlinear relationships, we used restricted cubic splines in the Cox proportional hazards model.To assess the predictive role of hsCRP on short-term (30 days) and long-term (3 years) mortality beyond conventional risk factors and troponin, we established 3 statistical models. Model 1 was adjusted for age, sex, haemoglobin, and creatinine; model 2 was additionally adjusted for troponin positivity; model and 3 was further adjusted for hsCRP . The statistical models were based on the predicted probabilities of a logistic regression model. Ethnicity was not included in the risk model due to approximately 10% of patients having missing data. Furthermore, for those who had ethnicity recorded, approximately 15% had “other” recorded as an ethnic category, therefore making it less easy to interpret as part of a clinical risk model.Discrimination of the different models was assessed by comparing the areas under the receiver operating characteristic curves (AUROCs) using the DeLong nonparametric approach. We also computed the continuous net reclassification index (NRI) and performed an integrated discrimination improvement (IDI) analysis with the censored survival data. Comparing the 3 models sequentially, the NRI reflects the net increment in prediction accuracy, while the IDI reflects the change in calculated risk for each individual. The IDI reflects the change in discrimination slope  of the model with the new predictor compared to the model with only the established predictors. IDI (range −100% to 100%) represents overall risk discrimination improvement.In order to evaluate the performance of negative hsCRP and troponin values in predicting mortality, the negative predictive values of a negative hsCRP, negative troponin, or both a negative troponin and hsCRP were plotted against the range of hypothetical mortality rates at 30 days and 3 years. The negative predictive value, which varies with the prevalence of disease , is defined as the probability of not dying when the test result is negative.Statistical analyses were performed using R 3.5.0  or MedCalc version 15.8 . The survIDINRI package on R was used to implement the IDI and NRI for comparing risk prediction models.9/L) or those who did not have a WCC blood test, 102,337 patients were included in the final analysis. The median follow-up was 3.3 years (IQR 1.4 to 5.1). The study cohort was divided into 4 hsCRP categories , 2 to 4.9 mg/L , 5 to 9.9 mg/L , and 10 to 15 mg/L ). Overall, 53.3%  of patients in the study cohort were admitted to the hospital. Among these patients, 10.8%  were coded with an ACS during their inpatient stay. Patient flow through the study is shown in A total of 257,948 patients presented with suspected ACS to 5 acute cardiac centres and were included in the NIHR Health Informatics Collaborative dataset. Moreover, 71,262 patients did not undergo hsCRP testing during their hospital care episode and were therefore excluded from further analysis. A further 67,206 patients were excluded based on hsCRP level >15 mg/L. The remaining 129,480 patients were divided into 4 groups by hsCRP levels, reflecting low grade inflammation. After further exclusion of patients with abnormal WCCs (<4 or >11 × 10p < 0.001) (< 0.001) . Althougp < 0.001). A similar relationship with hsCRP is seen in patients with different levels of troponin positivity , such that inclusion of troponin and hsCRP gave the most robust risk discrimination. Of note, model 3, which includes both troponin positivity and hsCRP categories, achieves an AUROC >0.8 at 30 days and 3-year mortality, surpassing the use of troponin on its own. The addition of model 3 over model 2 resulted in an IDI of 0.3% and 0.9% at 30 days and 3 years, respectively , as well as the highest overall NRI of 18.4% and 13.9% at the same time points, respectively . Thus, the inclusion of hsCRP to the basic model with troponin level significantly improved all-cause mortality risk prediction.We next explored whether inclusion of hsCRP could better reclassify the population into at-risk mortality groups. The association with short-term and long-term mortality was assessed using 3 different risk models ; and model 3: model 2 plus hsCRP groups  . For cumIn this large retrospective cohort study, we demonstrate a positive and graded relationship between mildly elevated hsCRP levels (up to 15 mg/L) and all-cause mortality over 3 years. The mortality risk associated with increased hsCRP was independent of age, sex, haemoglobin, WCC, platelet count, creatinine, and troponin positivity, suggesting its value as a clinically useful biomarker in the context of suspected ACS. Compared to a normal hsCRP (<2 mg/L), a mildly raised hsCRP between 10 and 15 mg/L was associated with a 2.2-fold increased mortality risk at 30 days, which persisted at 3 years. In this study, patients who had negative serum troponin but a hsCRP between 10 and 15 mg/L had equivalent mortality to those who were troponin positive but had a normal hsCRP, <2 mg/dL, in Kaplan–Meier analysis at 3 years. Moreover, patients were better reclassified into at-risk mortality groups when hsCRP was included in addition to troponin, suggesting a potential use in this clinical setting.We limited the cohort by prespecifying strict exclusion criteria that aim to reduce the numbers of patients with infective, inflammatory, or malignant disorders. Therefore, we excluded anyone with abnormal WCC or hsCRP >15 mg/L, with the aim of assembling a cohort that would be informative for clinicians treating patients with suspected ACS. This was possible due to the large population available for study.The key finding of this study was that within a group of patients with low levels of hsCRP elevation, there was a significant increase in mortality risk in patients presenting with suspected ACS in both the short and long term. In Cox regression analysis with time-dependent covariates, the highest hsCRP group had a HR 2.20 (95% CI 1.88 to 2.57) at baseline, which only marginally attenuated to 2.00 (95% CI 1.75 to 2.28) at 3 years. This long-term risk is clinically significant and may present an opportunity to improve patient selection for novel diagnostics and therapeutics. The striking finding that patients in the highest hsCRP group, but who were troponin negative, had similar mortality to those who were troponin positive but had hsCRP < 2 mg/L, brings into question whether, in clinical practice, we are missing high-risk patients who may benefit from further investigation and treatment . To expaThere has been a very positive response surrounding immunomodulatory drugs in CVD following publication of the CANTOS , COLCOT It is difficult in clinical practice to identify the exact time point when an ACS event occurs. The time of diagnosis may not coincide with the time of onset of the ACS event. In order to determine the effect of baseline hsCRP levels rather than hsCRP rises in response to an infarct, we carried out analyses on admission hsCRP levels in comparison to the “peak” troponin level in predicting mortality. For patients with an elevated troponin result, the median number of days between the first admission hsCRP measured and peak troponin level was 3 (IQR 0 to 5) days, infering that the admission hsCRP levels likely represent presentation values rather than the sequelae of the index event.p = 0.001) was also shown to be independently associated with MACE and mortality.We excluded individuals who had a CRP >15 mg/L  to limit the population to those without overt infections, malignancies, or systemic inflammatory conditions. It is unlikely that we excluded many patients with ACS due to the low CRP levels measured in patients with ACS in previous studies. In a recent study investigating the association of initial hsCRP levels with MACE and mortality after ACS , the medRecently, in the multicentre matched-control pilot study on CRP apheresis in Acute Myocardial Infarction (CAMI-1), there was a correlation between the CRP gradient between 12 and 32 hours after symptom onset and both myocardial infarct size and the extent of reduction in left ventricular function . The CAMMoreover, an interesting finding in the present study is that those with raised hsCRP and moderate troponin elevations had the greatest mortality risk. While there was a graded relationship between hsCRP level and mortality among patients with different levels of troponin positivity, the mortality risk in the hsCRP groups increased progressively up to >5 to 10×ULN of troponin and then progressively declined in the higher troponin groups. Previous research from our group has demonstrated this inverted U-shaped relation between troponin level and mortality in an unselected cohort of patients undergoing troponin testing. This was primarily due to an interaction between ACS diagnosis and differential receipt of invasive management in this cohort.  The >5 tThe observed discrimination and net reclassification when adding hsCRP to our risk models is an important new finding. There have been several studies showing the value of hsCRP as an added covariate for predicting long-term mortality risk in primary prevention populations or those with chronic CVD, leading to developments such as the Reynolds risk score, which improves on the widely adopted Framingham risk score . To our There are some limitations to this study. The present study had access to all-cause, but not specific, mortality data. This limits our ability to understand the causes of death in the patients with the higher hsCRP levels. However, the exclusion of those with abnormal WCC or hsCRP levels >15 mg/L makes it unlikely that sepsis was a major contributor to the excess mortality. Nonetheless, all-cause mortality is clearly a clinically relevant end point. A further limitation is the retrospective nature of the data, where covariates were collated from clinical records, rather than a prospective database that is designed to answer a predefined hypothesis. We were unable to determine the patient comorbidities for our cohort. The median age demographic of patients progressively increases from the lowest to the highest quartile of hsCRP. While we were unable to adjust our analyses by patient comorbidities, all survival analyses were adjusted for age, which may also act as a surrogate marker of patient comorbidities, which are expected to increase in frequency with older age.The data from this study emphasises the need for further prospective work that explores the inflammation pathway as a therapeutic target to address the still unanswered mortality gap in patients presenting with suspected ACS. We know that recurrent MACE in those undergoing percutaneous coronary intervention (PCI)  or preseThe data from this large real-world population in a modern healthcare system emphasise the importance of hsCRP in this setting and warrant attention and consideration from clinical guideline committees to include hsCRP in risk stratification of patients presenting with suspected ACS.The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.S1 ChecklistSTROBE, Strengthening the Reporting of Observational Studies in Epidemiology.(DOCX)Click here for additional data file.S1 Data Acquisition(DOCX)Click here for additional data file.S1 Analysis Plan(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableACS, acute coronary syndrome; ICD, International Classification of Diseases.(DOCX)Click here for additional data file.S3 TablehsCRP, high-sensitivity C-reactive protein.(DOCX)Click here for additional data file.S4 TableHR, hazard ratio; hsCRP, high-sensitivity C-reactive protein.(DOCX)Click here for additional data file.S1 FighsCRP, high-sensitivity C-reactive protein.(DOCX)Click here for additional data file.S2 FighsCRP, high-sensitivity C-reactive protein.(DOCX)Click here for additional data file.S3 FigACS, acute coronary syndrome.(DOCX)Click here for additional data file. 16 Sep 2021Dear Dr Hartley, Thank you for submitting your manuscript entitled "High sensitivity C-reactive protein predicts mortality beyond troponin in 102337 patients with suspected acute coronary syndrome" for consideration by PLOS Medicine.Your manuscript has now been evaluated by the PLOS Medicine editorial staff as well as by an academic editor with relevant expertise and I am writing to let you know that we would like to send your submission out for external peer review.However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. 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Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."http://www.equator-network.org/reporting-guidelines/strobe/The STROBE guideline can be found here: When completing the checklist, please use section and paragraph numbers, rather than page numbers.Comments from the reviewers:Reviewer #1: "High sensitivity C-reactive protein predicts mortality beyond troponin in 102337 patients with suspected acute coronary syndrome" studies the association of (mildly) elevated levels of high-sensitivity C-reactive protein (hsCRP) on long-term (3 year) mortality risk in patients with suspected acute coronary syndromes (ACS), independent of troponin level. The main analysis concluded that there was indeed a positive and graded relationship between hsCRP and mortality at baseline and over three years, as summarized in Figures 2B and 3. In particular, stratification by hsCRP level demonstrated increasing 3-year mortality risk given fixed troponin positivity/negativity status , and increased mortality over the full 3-year period by multivariable time-dependent Cox regression mortality analysis . hsCRP was therefore claimed to be a possible clinically prognostic marker in addition to troponin.While the primary association between hsCRP and mortality risk appears clear, a number of issues might be considered, largely towards clarifying the methodology:1. The definition of the upper limit of normal (ULN) for troponin assays might be explicitly stated, and the significance of "99th percentile of ULN" explained, especially since levels of troponin >100x ULN appear possible from Supplementary Figure 2. In particular, if ULN is the threshold on troponin level that separates troponin positive and negative diagnoses, then it would appear more natural to refer to the "99th percentile of troponin values" (to eliminate outliers at the upper end?); this might not be obvious to the more general reader.2. Moreover, it is stated that the different troponin assays from various academic centres were standardized by scaling results using the ratio of observed troponin value divided by the (unique) ULN for each troponin assay. It might be clarified as to how the ULN for each troponin assay was determined. Is this ULN inherent to the troponin assay model, or empirically calculated on some cohort? Also, were such  normalizations significant?3. Supplementary Figure 2 shows sensitivity analyses comparing the mortality curves for different definitions of troponin positivity . It appears that overall mortality risk is generally highest for 5-10x ULN, and actually lower for >100x ULN, than 1-5x ULN, i.e. the association of troponin level with mortality risk is nonlinear . If so, it might be discussed in greater detail as to whether this nonlinear association is expected, and its possible causes.4. It is stated that the data model involves patients with suspected ACS, as characterized by the request of a troponin test. It might be clarified as to whether this set of patients with troponin test results corresponds to the n=257,948 patients of the initial cohort , and whether the troponin test is exclusively administered towards suspected ACS.5. It is stated that n=134,517 patients were admitted to hospital and thus had ICD discharge codes, and patients were classified as ACS based on said ICD-10 codes. It might be clarified as to how and where this n=134,517 can be represented in the patient flowchart 6. It is stated that three statistical risk models were developed for mortality risk prediction (Table 2). The details of these models might be clarified - i.e. are they linear/logistic regression models , or other machine learning models, etc. Also, the choice of variables to match for/adjust for (e.g. ethnicity not included) might be briefly justified.7. For the Kaplan-Meier analysis in Figure 2, it might be explicitly stated if any matching/adjustment was attempted. The "No. at risk" matrices might also be briefly explained/defined.8. For Figure 3, it might be considered to provide additional time-dependent Cox regression mortality analysis charts stratified on troponin positivity/negativity, for consistency with the previous Kaplan-Meier analysis in Figure 2.9. Further on Figure 3, the time-dependent analysis would appear to require data from patients at each follow-up interval over the full 3-year period, whereas there does not appear to be a description for the treatment of patients with missing/incomplete data, in Figure 1 and elsewhere. It might be clarified whether all required data was available for all patients involved, or if not, how missing data was handled 10. Figure 4 might be explained in greater detail, with "negative predictive value" in particular being clarified.11. In the Results section, it is stated that "...Although we tested hsCRP in relation to peak troponin available in predicting mortality, we established that the median number of days between first troponin test and hsCRP was 0 (IQR 0), indicating that our hsCRP and troponin values represent presentation values rather than the sequelae of the index event". The significance of this statement might be clarified further. Does it imply that peak troponin is generally attained on the first test?12. The claim of "...The independence of hsCRP from all other available covariates including troponin in predicting mortality" in the Discussion section, might be supported with more specific data.Minor comments:13. The emphasis on "mildly elevated hsCRP" in describing association with mortality risk might be clarified; from Figure 2, it appears that the association exists over a large range of hsCRP elevation.14. Assessment of hsCRP independent of troponin level is also variously referred to as "beyond troponin" (in the title) and "above troponin" (in the abstract). It might be considered to standardize the terminology throughout, for clarity.15. In the Statistical Analysis section, it is stated that "the IDI reflects the change in calculated risk for each individual"; it might be clarified as to whether this change is positive by default (i.e. improvement).Reviewer #2: This paper describes the incremental long-term prognostic value of high-sensitivity C-reactive protein (hsCRP) above troponin in a large real-world cohort of unselected ACS patients. The objective was to determine if mildly elevated hsCRP was associated with mortality risk, irrespective of troponin level. Eligible patients from 2010 until 2017 were included retrospectively, utilizing NIH Research Health Informatics Collaborative data collected from five hospital centers in Great Britain. Patient selection was based on troponin measurements, normal white blood cell counts and a hsCRP up to 15 mg/L. Patients were followed up until death or censoring within 3 years. To standardize, the ratio of the observed peak troponin value was divided by the ULN for each troponin assay. 102337 patients were included in the analysis. The population was divided into four categories, those with a normal hsCRP <2mg/L, and three groups of incrementally increasing hsCRP . On multivariable Cox regression analysis, there was a positive and graded relationship between hsCRP level and mortality at baseline, which remained at three-years, irrespective of troponin values. The background for this mega-study is based on the hypothesis that inflammation is a contributory factor for the development of atherosclerosis, supported by RCTs, such as CANTOS, COLCOT and LoDoCo2, the former applying canakinumab and the two latter applying colchicine as anti-inflammatory agents, whereas no effect of methotrexate was obtained in CIRT. These trials were performed in patients with established coronary heart disease, with cardiovascular disease as a primary endpoint, reflecting progression of atherosclerotic disease, whereas the current study presents results related to total mortality, which also includes non-cardiac death, and, ideally, this should have been accounted for when discussing the significance of hsCRP as a marker of atherosclerotic disease. As patients in the highest as compared to the lowest quartile of hsCRP are 10 years older, one would expect an increasing proportion of co-morbidity through the quartiles of this observational study. These limitations are essential, especially when relating the results to progressive atherosclerotic disease and recommending hsCRP for selection of high-risk patients that may benefit from anti-inflammatory treatment. Hs-CRP is an acute phase reactant and may not be a reliable indicator of risk, when not measured during steady state. However, the observation that mortality was greatest in patients with raised hs-CRP and moderate troponin elevations, might support the authors' claim.In short, discussion and limitations require more attention.Reviewer #3: This manuscript describes the importance of measuring hsCRP in ACS patients as prognostic factor in a large patient cohort. This research question is crucial to further provide information on patient selection for anti-inflammatory therapies and early prognosis of deleterious outcomes. The main claims are that CRP admission levels of suspected and actual ACS patients significantly correlate with 30-day and 3-year mortality of these patients. It is therefore concluded that CRP should be routinely assessed in ACS patients and not discarded as only a systemic inflammation marker. Together with troponin, risk assessment of ACS patients could be easily improved. Minor points:1) The authors should discuss critically and in more detail that all data analysis is based on the initial hsCRP value at hospital admission. They write "that our hsCRP and troponin values represent presentation values rather than sequelae of the index event". The authors should put this in the context of recent publications regarding CRP's active role in the pathophysiology of acute coronary incidents such as AMI and the acute phase response in general. Is there information of the exact time point of CRP measurement and actual diagnosed ACS? This could enlighten whether it is actually the CRP baseline value or already the initial increase of the acute phase response. By excluding patients with CRP > 15 mg/L not only infections but also already ongoing acute coronary events were excluded. The authors also do not mention that in the CAMI-1 trial, a significant association was found between CRP gradient (CRP increase between 12 and 32 hours after symptom onset) and infarct size, LVEF, and circumferential and longitudinal strain. In addition, some publications reported a significant correlation between infarct size and peak CRP, which could also be used as a predictor (most from University of Innsbruck). Both could be discussed in relation to the use of CRP level on admission. In the context of a 2016 meta-analysis showing a significant association between infarct size and mortality , another point could be discussed.2) Given the strong evidence for the pathophysiological effect of a high CRP level, the following statement in the manuscript could be supplemented by citing recent literature: "The striking finding that patients in the highest hsCRP group, but who were troponin-negative, had similar mortality to those who were troponin-positive but had hsCRP<2 mg/L, brings into question whether, in clinical practice, we are missing high-risk patients who may benefit from further investigation and treatment."3) Following this, the authors should also introduce CRP not only as end-protein read-out of the IL-6 cascade. They write this in the context of atherosclerosis and baseline CRP levels but should include CRP's pathophysiological role during and after acute incidents.4)The statistical methods are well described and mostly appropiate. Among others, the continuous NRI and IDI are used to show the improvement in the prediction model, when hsCRP and troponin positivity are added and p-values are calculated. Continuous NRI and IDI are frequently used, but also prone to error, especially if nested models are used and p-values are calculated . The continuous NRI and IDI could be used to describe the improvement of the model, but likelihood-based methods should be used to calculate p-values .Since there are already significant differences in the AUROC for the different models and there is a clear improvement in NRI and IDI, it is very likely, that the likelihood-based calculation will support the improvement of the models.Literature:Pepe et al. 2013: Testing for improvement in prediction model performance, Stat Med. 2013 Apr 30; 32(9): 1467-1482.Pepe et al. 2014: Net Risk Reclassification P Values: Valid or Misleading?, J Natl Cancer Inst. 2014 Apr; 106(4): dju041.Pencina et al. 2015: RE: net risk reclassification P Values: valid or misleading?, J Natl Cancer Inst. 2014 Nov 27;107(1):355.Burch et al. 2017: Net Reclassification Index and Integrated Discrimination Index Are Not Appropriate for Testing Whether a Biomarker Improves Predictive Performance, Toxicol Sci. 2017 Mar; 156(1): 11-13.Any attachments provided with reviews can be seen via the following link:[LINK] 1 Dec 2021AttachmentResponse to Reveiwer Document.docxSubmitted filename: Click here for additional data file. 23 Dec 2021Dear Dr. Mayet,Thank you very much for re-submitting your manuscript "The mortality risk prediction of mildly elevated high-sensitivity C-reactive protein beyond troponin in 102337 patients with suspected acute coronary syndrome : A retrospective cohort study" (PMEDICINE-D-21-03948R2) for review by PLOS Medicine.I have discussed the paper with my colleagues and the academic editor and it was also seen again by two reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:[LINK]***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. 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Key information to include: study design, population and setting, number of participants, years during which the study took place, length of follow up, main outcome measures, quantified main results , and important dependent variables adjusted for in the analyses. Additional methodological detail  can be removed. Additionally, you can remove the content from ‘All analyses on hsCRP…’ to ‘…using the peak troponin level’ in paragraph two of the abstract methods and findings (lines 24-27). Please also condense the ‘limitations’ section of the abstract (lines 10-13) such that it is only a single sentence beginning ‘The main limitations of the study are’, or similar. Given the observational nature of your study, I suggest updating the first sentence of the abstract conclusions to read ‘These multi-centre, real-world data from a large cohort of patients with suspected ACS suggest mildly elevated hsCRP (up to 15 mg/L) may be a clinically meaningful prognostic marker beyond troponin and point to its potential utility in selecting patients for novel treatments targeting inflammation.’The Data Availability Statement (DAS) requires revision. If the data are not freely available, please describe briefly the ethical, legal, or contractual restriction that prevents you from sharing it. Please also include an appropriate contact (web or email address) for inquiries (this cannot be a study author). https://journals.plos.org/plosmedicine/s/revising-your-manuscript) and consult previous PLOS Medicine articles for examples . Please update your Author Summary using the standard PLOS Medicine structure. 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The primary study objective of this retrospective academic memory clinic-based observational longitudinal study was to investigate the prognostic value of a cerebrospinal fluid (CSF)-based ATN classification for subsequent cognitive decline during the 3 years following lumbar puncture in a clinical, real-life setting. The secondary objective was to investigate the prognostic value of CSF biomarkers as continuous variables.42), hyperphosphorylated tau (p181-tau) and total tau (t-tau) in the clinical work-up for diagnostic reasons. Patients were divided into ATN classes based on CSF biomarkers: Aβ42 for amyloid (A), p181-tau for tau (T), and t-tau as a measure for neurodegeneration (N). Based on retrospective data analysis, cognitive performance was evaluated by Mini Mental State Examination (MMSE) scores every 6 months over a period up to 36 months following the lumbar puncture. The statistical analysis was based on linear mixed-effects modeling (LME).Data from 228 patients (median age 67 (47–85) years), who presented at the Neurology Memory Clinic UZ/KU Leuven between September 2011 and December 2016, were included with a follow-up period of up to 36 months. Patients underwent a CSF AD biomarker test for amyloid-beta 1–42 , with no cases in the A−/T+/N− and A+/T+/N− class. Hence, the latter 3 classes were excluded from further analyses. The change of MMSE relative to A−/T−/N− over a 36-month period was significant in all four ATN classes: A+/T+/N+ = − 4.78 points on the MMSE; A−/T−/N+ = − 4.76; A+/T−/N+ = − 2.83; A+/T−/N− = − 1.96. The earliest significant difference was seen in the A+/T+/N+ class at 12 months after baseline. The effect of ATN class on future cognitive decline was confirmed for a different set of CSF thresholds. All individual baseline CSF biomarkers including the AβATN classification based on CSF biomarkers has a statistically significant and clinically relevant prognostic value for the course of cognitive decline in a 3-year period in a clinical practice setting.The online version contains supplementary material available at 10.1186/s13195-021-00817-4. Alzheimer’s disease (AD) is the most frequent cause of dementia, with a prevalence of approximately 0.2–0.9% in the age group of 60–64 years old, with an exponential increase to 10.7–13.1% in the age group of 80–84 years old fluodeoxyglucose PET ([18F]FDG-PET) or atrophy on magnetic resonance imaging (MRI). This ATN classification scheme is an unbiased descriptive system which can be applied to all patients, without being coupled to a specific diagnosis. The goal of this new classification system is to get insight in the evolution of the biomarkers in AD and eventually be able to make an early  biomarker-based diagnosis. Initially, it was intended for use in a research context, here we examine the prognostic value of this classification scheme in a clinical practice setting.In 2016, Jack et al.  proposed42, precedes the spread of tau aggregates, neurodegeneration and cognitive decline FDG-PET as well as CSF AD biomarker analysis. In the total group included in this report, the final clinical diagnosis was AD in 46.05% of cases. Other neurodegenerative disorders were diagnosed in 16–17% of patients  in 9.2%, Lewy Body disease in 4.4%, corticobasal syndrome in 1.8%, progressive supranuclear palsy in less than 1%), a non-neurodegenerative disorder in 28–29% of patients , and no clear diagnosis could be made in 8–9% of patients  scale (/30)  in a per18F]flutemetamol PET (amyloid-PET) as gold standard of amyloid-positivity flutemetamol amyloid-PET positivity as gold standard. This is based on the neuropathological validity of [18F]flutemetamol PET for the detection of moderate-to-high density of neuritic plaques AV1451 at the moment FDG-PET. In 2017, a renewed clinical cognitive evaluation was comparable to prior evaluations. Apart from the last two cases, these are all known causes of isolated t-tau increase.As expected, positivity for pThe A−/T−/N+ class shows a pronounced deterioration of MMSE over the 3-year follow-up period, which is driven by the patients diagnosed with corticobasal syndrome. This is a rapidly progressive neurodegenerative disorder with a survival rate of on average only 4–5 years . Of the 42/t-tau ratio as well as the individual CSF biomarkers showed a significant correlation with the time course of cognitive decline  and steep cognitive decline.The baseline Aβne Table , Fig. 3.An important point to emphasize is that these CSF biomarkers seem to have a prognostic value, independent of the final clinical diagnosis. In a recent study by Selvackadunco et al. , clinicaThe current study demonstrates that CSF biomarker measurements can have not only a diagnostic added value, but can also have important relevance for determining the prognosis of cognitive evolution. These CSF biomarkers have been shown to correlate with cognitive evolution in multiple trials before, both in cognitive normal individuals –27 as in181-tau in CSF, “N” based on medial temporal atrophy on MRI). Altomare et al. FDG-PET imaging techniques. An inherent disadvantage from the ATN classification is its binary division into classes, while the values of CSF biomarkers include a continuous value, which can be more informative. The necessity to define a cut-off to classify cases is also problematic for the ATN classification. The biological variable does not have a binary distribution, and furthermore, given the inter-laboratory variability of CSF AD biomarker assays and the absence of a neuropathological gold standard, cut-offs may vary between laboratories which impacts on the ATN classification. It is however worth noting that our conclusions remained when we varied the exact p181-tau and t-tau cut-offs. Finally, due to the low sample size of some ATN classes, a comprehensive evaluation of the 8 ATN classes was not feasible.The ATN classification can be based on multiple biomarkers, including CSF biomarkers but also imaging techniques. In our study, we only used CSF biomarkers and analyzed them in a single laboratory, consistently using the same immuno-assay to classify the patients. Although results from CSF biomarkers can vary between different laboratories, it seems to be more reproducible and less rater-dependent relative to results from MRI or [42/t-tau ratio showed a significant correlation with cognitive decline. The highest correlation was seen for the CSF Aβ42/t-tau ratio. Further confirmation of these results in prospective analyses is needed.Based on this retrospective analysis, ATN classification based on CSF biomarkers seems to have a statistical but also clinically relevant prognostic value for the course of cognitive decline over a 3-year period. Relative to the A−/T−/N− class, MMSE declines strongly in patients with the A+ biomarker but surprisingly also in the neurodegeneration-only (A−/T−/N+) group. All individual CSF biomarkers and the CSF AβAdditional file 1: Supplementary Table 1. Difference in MMSE at different time points relative to the reference class (A-/T-/N-) and to the baseline MMSE using linear mixed-effects model with random slope and imputation of missing values. The following CSF thresholds were used: 798 pg/mL for Aβ42, 87 pg/mL for p181-tau, 465 pg/mL for t-tau. Supplementary Table 2. Difference in MMSE at different time points relative to the reference class (A-/T-/N-) and to the baseline MMSE using linear mixed-effects model with random slope. The following CSF thresholds were used: 798 pg/mL for Aβ42, 58.9 pg/mL for p181-tau, 354 pg/mL for t-tau. Supplementary Table 3. Difference in MMSE at different time points relative to the reference class (A-/T-/N-) and to the baseline MMSE using linear mixed-effects model with random slope and imputation of missing values. The following CSF thresholds were used: 798 pg/mL for Aβ42, 58.9 pg/mL for p181-tau, 354 pg/mL for t-tau. Supplementary Table 4. Interaction of individual CSF biomarkers on evolution of MMSE using linear mixed-effects model and imputation of missing values. Supplementary Table 5. Distribution of syndrome diagnoses at the moment of the lumbar puncture per ATN class, based on the following cut-off values: 798 pg/mL for Aβ42, 87 pg/mL for p181-tau, 465 pg/mL for t-tau. MCI = mild cognitive impairment. Supplementary Table 6. Difference in MMSE at different time points relative to the reference class (A-/T-/N-) and to the baseline MMSE using linear mixed-effects model with random slope for patients with a syndrome diagnosis of mild cognitive impairment. The following CSF thresholds were used: 798 pg/mL for Aβ42, 87 pg/mL for p181-tau, 465 pg/mL for t-tau. Supplementary Table 7. Difference in MMSE at different time points relative to the reference class (A-/T-/N-) and to the baseline MMSE using linear mixed-effects model with random slope for patients with a syndrome diagnosis of dementia. The following CSF thresholds were used: 798 pg/mL for Aβ42, 87 pg/mL for p181-tau, 465 pg/mL for t-tau. Supplementary Table 8. Distribution of final etiological diagnoses per ATN class based on the clinical-diagnostic investigation including cerebrospinal fluid biomarkers. AD = Alzheimer’s disease. Other neurodeg = non-AD neurodegenerative disorders, including FTD , LBD (Lewy Body disease) and CBS . Non-neurodeg = no neurodegenerative disorders. ‘No diagnosis’ is reserved for patients without a clear diagnosis after standard clinical work-up.