Nanoscale field-effect transistors (FETs) represent a unique platform for real time, label-free transduction of biochemical signals with unprecedented sensitivity and spatiotemporal resolution, yet their translation toward practical biomedical applications remains challenging. Herein, we demonstrate the potential to overcome several key limitations of traditional FET sensors by exploiting bioactive hydrogels as the gate material. Spatially defined photopolymerization is utilized to achieve selective patterning of polyethylene glycol on top of individual graphene FET devices, through which multiple biospecific receptors can be independently encapsulated into the hydrogel gate. The hydrogel-mediated integration of penicillinase was demonstrated to effectively catalyze enzymatic reaction in the confined microenvironment, enabling real time, label-free detection of penicillin down to 0.2 mM. Multiplexed functionalization with penicillinase and acetylcholinesterase has been demonstrated to achieve highly specific sensing. In addition, the microenvironment created by the hydrogel gate has been shown to significantly reduce the nonspecific binding of nontarget molecules to graphene channels as well as preserve the encapsulated enzyme activity for at least one week, in comparison to free enzymes showing significant signal loss within one day. This general approach presents a new biointegration strategy and facilitates multiplex detection of bioanalytes on the same platform, which could underwrite new advances in healthcare research.

Abstract. Acute transverse myelitis is a rare manifestation of dengue infection. To the best of our knowledge, only 6 cases of acute transverse myelitis as a manifestation of dengue infection have been reported thus far. The present study described a case of acute transverse myelitis complicated with subacute thyroiditis 6 days after the onset of dengue viral infection. In addition, the available literature was searched to identify similar previous cases. Treatment with intravenous pulse methylprednisolone immunoglobulin plasmapheresis and physiotherapy resulted in partial recovery at 3 months post-infection. In conclusion, the involvement of dengue infection should be considered in patients who develop central nervous system manifestations during or after the recovery period of dengue infection. Furthermore, since methylprednisolone and immunoglobulin are effective during the active phase of the infection, prompt diagnosis and initiation of treatment are crucial.

Background: The Charlson Comorbidity Index (CCI) can be automatically calculated from the International Classification of Disease (ICD) code. However, the feasibility of this transformation has not been acknowledged, particularly in hospitals without a qualified ICD coding system. Here, we investigated the utility of coding-based CCI in China. Methods: A multi-center, population-based, retrospective observational study was conducted, using a dataset incorporating 2,464,395 adult subjects from 15 hospitals. CCI was calculated using both ICD-10-based and diagnosisbased method, according to the transformation rule reported previously and to the literal description from discharge diagnosis, respectively. A κ coefficient of variation was used as a measure of agreement between the above two methods for each hospital. The discriminative abilities of the two methods were compared using the receiver-of-operating characteristic curve (ROC) for prediction of in-hospital mortality. Results: Total agreement between the ICD-based and diagnosis-based CCI for each index ranged from 86.1 to 100%, with κ coefficients from 0.210 [95% confidence interval (CI) 0.208-0.212] to 0.932 (95% CI 0.924-0.940). None of the 19 indices of CCI had a κ coefficient > 0.75 in all the hospitals included for study. The area under the curve of ROC for inhospital mortality of all 15 hospitals was significantly lower for ICD-based than diagnosis-based CCI [0.735 (0.732, 0.739) vs 0.760 (0.757, 0.764)], indicative of more limited discriminative ability of the ICD-based calculation. Conclusions: CCI calculated using ICD-10 coding did not agree with diagnosis-based CCI. ICD-based CCI displayed diminished discrimination performance in terms of in-hospital mortality, indicating that this method is not promising for CCI scoring in China under the present circumstances.

Background: The study aimed to construct a clinical model based on preoperative data for predicting acute kidney injury (AKI) following cardiac surgery in patients with normal renal function. Methods: A total of 22,348 consecutive patients with normal renal function undergoing cardiac surgery were enrolled. Among them, 15,701 were randomly selected for the training group and the remaining for the validation group. To develop a model visualized as a nomogram for predicting AKI, logistic regression was performed with variables selected using least absolute shrinkage and selection operator regression. The discrimination, calibration, and clinical value of the model were evaluated. Results: The incidence of AKI was 25.2% in the training group. The new model consisted of nine preoperative variables, including age, male gender, left ventricular ejection fraction, hypertension, hemoglobin, uric acid, hypomagnesemia, and oral renin-angiotensin system inhibitor and nonsteroidal anti-inflammatory drug within 1 week before surgery. The model had a good performance in the validation group. The discrimination was good with an area under the receiver operating characteristic curve of 0.740 (95% confidence interval, 0.726-0.753). The calibration plot indicated excellent agreement between the model prediction and actual observations. Decision curve analysis also showed that the model was clinically useful. Conclusions: The new model was constructed based on nine easily available preoperative clinical data characteristics for predicting AKI following cardiac surgery in patients with normal kidney function, which may help treatment decision-making, and rational utilization of medical resources.