Human exposure risk assessment for infectious diseases due to temperature and air pollution: an overview of reviews.

Air pollution and global temperature change are expected to affect infectious diseases. Air pollution usually causes inflammatory response and disrupts immune defense system, while temperature mainly exacerbates the effect of vectors on humans. Yet to date overview of systematic reviews assessing the exposure risk of air pollutants and temperature on infectious diseases is unavailable. This article aims to fill this research gap. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature were searched. Systematic reviews and meta-analyses investigated the exposure risk of pollutants or temperature on infectious diseases were included. Two investigators screened literature, extracted data and performed the risk of bias assessments independently. A total of 23 articles met the inclusion criteria, which 3 (13%) were "low" quality and 20 (87%) were "critically low" quality. COVID-19 morbidity was associated with long-term exposure PM2.5 (RR = 1.056 per 1 [Formula: see text], 95% CI: 1.039-1.072) and NO2 (RR = 1.042 per 1 [Formula: see text], 95% CI: 1.017-1.068). In addition, for each 1 °C increase in temperature, the morbidity risk of dengue increased 13% (RR = 1.130 per 1 °C, 95% CI: 1.120-1.150), infectious diarrhea increased 8% (RR = 1.080 per 1 °C, 95% CI: 1.050-1.200), and hand, foot and mouth disease (HFMD) increased 5% (RR = 1.050 per 1 °C, 95% CI: 1.020-1.080). In conclusion, PM2.5 and NO2 increased the risk of COVID-19 and temperatures were associated with dengue, infectious diarrhoea and HFMD morbidity. Moreover, the exposure risk of temperature on COVID-19 was recommended to be further explored.

Assessment of chronic allograft injury in renal transplantation using diffusional kurtosis imaging.

BACKGROUND: Chronic allograft injury (CAI) is a significant reason for which many grafts were lost. The study was conducted to assess the usefulness of diffusional kurtosis imaging (DKI) technology in the non-invasive assessment of CAI. METHODS: Between February 2019 and October 2019, 110 renal allograft recipients were included to analyze relevant DKI parameters. According to estimated glomerular filtration rate (eGFR) (mL/min/ 1.73 m2) level, they were divided to 3 groups: group 1, eGFR ≥ 60 (n = 10); group 2, eGFR 30-60 (n = 69); group 3, eGFR < 30 (n = 31). We performed DKI on a clinical 3T magnetic resonance imaging system. We measured the area of interest to determine the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) of the renal cortex and medulla. We performed a Pearson correlation analysis to determine the relationship between eGFR and the DKI parameters. We used the receiver operating characteristic curve to estimate the predicted values of DKI parameters in the CAI evaluation. We randomly selected five patients from group 2 for biopsy to confirm CAI. RESULTS: With the increase of creatinine, ADC, and MD of the cortex and medulla decrease, MK of the cortex and medulla gradually increase. Among the three different eGFR groups, significant differences were found in cortical and medullary MK (P = 0.039, P < 0.001, P < 0.001, respectively). Cortical and medullary ADC and MD are negatively correlated with eGFR (r = - 0.49, - 0.44, - 0.57, - 0.57, respectively; P < 0.001), while cortical and medullary MK are positively correlated with eGFR (r = 0.42, 0.38; P < 0.001). When 0.491 was set as the cutoff value, MK's CAI assessment showed 87% sensitivity and 100% specificity. All five patients randomly selected for biopsy from the second group confirmed glomerulosclerosis and tubular atrophy/interstitial fibrosis. CONCLUSION: The DKI technique is related to eGFR as allograft injury progresses and is expected to become a potential non-invasive method for evaluating CAI.

Transition and Dynamic Reconfiguration of Whole-Brain Network in Major Depressive Disorder.

Major depressive disorder (MDD) has been characterized by abnormal brain activity and interactions across the whole-brain functional networks. However, the underlying alteration of brain dynamics remains unclear. Here, we aim to investigate in detail the temporal dynamics of brain activity for MDD, and to characterize the spatiotemporal specificity of whole-brain networks and transitions across them. We developed a hidden Markov model (HMM) analysis for resting-state functional magnetic resonance imaging (fMRI) from two independent cohorts with MDD. In particular, one cohort included 127 MDD patients and 117 gender- and age-matched healthy controls, and the other included 44 MDD patients and 33 controls. We identified brain states characterized by the engagement of distinct functional networks that recurred over time and assessed the dynamical configuration of whole-brain networks and the patterns of activation of states that characterized the MDD groups. Furthermore, we analyzed the community structure of transitions across states to investigate the specificity and abnormality of transitions for MDD. Based on our identification of 12 HMM states, we found that the temporal reconfiguration of states in MDD was associated with the high-order cognition network (DMN), subcortical network (SUB), and sensory and motor networks (SMN). Further, we found that the specific module of transitions was closely related to MDD, which were characterized by two HMM states with opposite activations in DMN, SMN, and subcortical areas. Notably, our results provide novel insights into the dynamical circuit configuration of whole-brain networks for MDD and suggest that brain dynamics should remain a prime target for further MDD research.

Impact of pharmacist-led post-transplant medication management for kidney transplant recipients: A retrospective pre- and post-intervention study.

WHAT IS KNOWN AND OBJECTIVE: The roles of pharmacists in medication management for transplant recipients have received limited attention. This study comprehensively assessed the impact of pharmacist-led post-transplant medication management. METHODS: A retrospective pre- and post-intervention study was conducted in the urology ward in a general hospital. Patients receiving kidney transplants from May 2015 to April 2017 were enrolled. Eligible subjects were assigned into two groups (pre-intervention group and post-intervention group) according to the date (1 May 2016) when the pharmacist commenced participation in the post-transplant management for kidney transplant recipients. The outcomes included intervention analysis, cost-saving effect, outcomes of immunosuppressive drug level monitoring, antibiotic outcomes, safety outcomes, and blood pressure (BP) and plasma glucose (PG) outcomes. RESULTS AND DISCUSSION: A total of 299 patients were admitted to our hospital for kidney transplantation. Two hundred and four patients met inclusion criteria for this study (84 patients were in pre-intervention group, and 120 patients were in post-intervention group). Out of 630 pharmacist interventions in the medication order, 97.1% were accepted by the physicians. The average cost of medications per patient decreased from 4661.64 Ren Min Bi (RMB) to 3051.33 RMB. The percentage of patients who maintained tacrolimus (TAC) levels within the target concentration range was higher in the post-intervention group on post-operative day (POD) 7 (75.00% vs 87.50%, P = 0.021). There was a significant decrease in antibiotic use density (AUD) and duration of antibiotic treatment in the post-intervention group. Post-intervention group showed lower levels in systolic blood pressure (SBP) (141.55 ± 14.62 vs 136.04 ± 13.17, P = 0.01) with higher BP control rate (67.50% vs 90.70%, P = 0.00) on discharge day compared to pre-intervention group. WHAT IS NEW AND CONCLUSION: Pharmacists played a comprehensive role in the management of kidney transplant recipients in the inpatient setting, with some evidence of enhanced clinical outcomes.

Assessment of postoperative perfusion with contrast-enhanced ultrasonography in kidney transplantation.

The aim of this study was to use contrast-enhanced ultrasound (CEUS) to evaluate renal perfusion after kidney transplantation and investigate the clinical significance of CEUS in monitoring postoperative renal perfusion. Thirty-five patients who underwent kidney transplantations were included in this study and divided into two groups-normal and abnormal-based on their serum creatinine (SCr) levels. Conventional ultrasound and CEUS were used to monitor renal perfusion after kidney transplantation. The differences in the results between the two groups were then compared. Color doppler ultrasonography showed that there were significant differences in the resistance index (RI) and the pulsatility index (PI) of the interlobar artery between the groups. Furthermore, CEUS indicated a significant difference between the two groups regarding the slope rate of the cortical ascending curve (A1), the medullary ascending curve (A2), and the derived peak intensity (DPI1). CEUS precisely showed the characteristics of microcirculation in renal parenchyma after kidney transplantation. It also detected changes in the microcirculation, which was a new method of evaluating tissue perfusion in transplanted kidneys.

The use of visual search for knowledge gathering in image decision support.

This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.