Photodynamic therapy-a promising treatment of oral mucosal infections

The treatment of oral mucosal infections is increasingly challenging owing to antibiotic resistance. Therefore, alternative antimicrobial strategies are urgently required. Photodynamic therapy (PDT) has attracted attention for the treatment of oral mucosal infections because of its ability to effectively inactivate drug-resistant bacteria, completely heal clinical infectious lesions and usually offers only mild adverse reactions. This review briefly summarizes relevant scientific data and published papers and discusses the potential mechanism and application of PDT in the treatment of oral mucosal infections.     

Higher smoking prevalence among United States adults with co-occurring affective and drug use diagnoses

IntroductionIndividuals with drug use disorders or affective disorders have higher cigarette smoking prevalence and smoking intensity and are less likely to quit than the general population. We sought to estimate the prevalence of cigarette smoking by drug use and psychiatric diagnoses and to explore to what extent a co-occurring diagnosis was associated with current smoking.MethodsData were derived from the most recent National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III, 2012–2013; n = 36,309). Cigarette smoking status was examined among those with any past-year or lifetime drug use disorders (i.e., alcohol, cannabis, opioid, cocaine) or affective disorders (i.e., mood, anxiety). Diagnoses were assessed using the Diagnostic and Statistical Manual of Mental Disorders criteria (DSM-5).ResultsAdjusting for sociodemographic characteristics, those with drug use disorders (past-year AOR = 3.3, 95% CI: 3.0, 3.6; lifetime AOR = 3.2, 95% CI: 3.0, 3.5) and those with affective disorders (past-year AOR = 1.7; 95%CI: 1.5, 1.8, lifetime AOR = 1.3, 95% CI: 1.2; 1.4), had higher odds of current cigarette smoking compared to individuals with no diagnosis. The odds of current cigarette smoking was significantly higher in individuals with both drug use disorders and affective disorders compared to those with either a drug use or affective disorder or no disorder (past-year AOR = 5.1; 95% CI: 4.3, 5.9, lifetime AOR = 4.3; 95% CI: 3.8, 4.7).ConclusionsApproximately 30% of the population had a past-year drug use or affective disorder, 17% of whom report both. The combination of both diagnoses produced a 1.5 to 3-fold higher correlation with smoking than either alone.     

Mechanisms and clinical course of cardiovascular toxicity of cancer treatment I. Oncology

The opening session of Second International Colloquium on Cardio-Oncology addressed two areas of vital interest. The first reviewed new thoughts related to established agents. While anthracycline cardiotoxicity has been studied and reviewed extensively, ongoing research attempting to understand why it appears the mechanism(s) of toxicity differs from that of oncologic efficacy continue to evoke comment and intriguing speculation. Better understanding of the role of β-topoisomerase II in toxicity has advanced our understanding of the cascade of events that lead to heart failure. Additionally, the cardioprotective role of dexrazoxane fits well with our new understanding of how β-topoisomerase II works. Beyond the anthracyclines, new insight is providing us insight to better understand the impact on cardiac function seen with other agents including those targeting HER2 and several tyrosine-kinase inhibitors. Unlike the anthracyclines, these agents affect cardiac function in ways that are less direct, and therefore have different characteristics and should be thought of in alternate ways. This new knowledge regarding established agents furthers our understanding of the spectrum of cardiotoxicity and cardiac dysfunction in the cancer patient. The session also addressed cardiovascular toxicities of newer and established agents beyond myocardial dysfunction including effects on the vasculature. These agents cause changes that may be temporary or permanent, and that range from subclinical to life-threatening. The session ended with a discussion of the cardiac effects of immune checkpoint inhibitors. These agents can cause rare and sometimes fatal cardiac inflammation, for which long-term follow up may be required.     

Analysis of the fluid biochemistry in patients with prolonged wound drainage after hip hemiarthroplasty

IntroductionThe origin and content of prolonged wound drainage (PWD) after arthroplasty remain uncertain. In this study, we performed the biochemical, biological and advanced proteomic analysis of the drainage fluid collected from PWD patients following hip hemiarthroplasty (HA).MethodsData of 28 patients who developed PWD after HA were prospectively analyzed. After examining the biochemical content of the drainage fluid collected on postoperative day 6, to find out if the drainage fluid was transudate or exudate, it was compared with the patient's serum values according to the Light criteria. Subsequently, biological and proteomic analyzes of both drainage fluid and serum were performed. The similarities and differences in terms of protein concentrations, protein identities were examined. In the drainage fluid, we analyzed lymph-specific proteins.Results16 patients with PWD were male (61.1%), 12 were female (38.9%), and the mean age of all patients was 79.64 ± 8.44 (65-95). Biochemical test results of the drainage fluid / serum were as follows: Total protein: 2.1 / 5.2 g/dl, albumin: 1.3 / 3.1 g/dl, lactate dehydrogenase (LDH): 121/324 U/l, cholesterol: 28/160 mg/dl, triglyceride: 37/122 mg/dl, sodium (Na): 140/ 140mg/dl, potassium (K): 4.1/ 4.1 mg/dl. pH of the drainage fluid was 7.6. According to these biochemical values, drainage fluid was classified as transudate. As a result of protein identification, fibrinogen beta chain, keratin type 1, creatine kinase M-type protein were detected in drainage fluid. Subsequent western analysis revealed that, gliseraldehyde-3-phosphate dehydrogenase (GAPDH) and beta actin antibody were detected in the drainage fluid but not in serum.ConclusionDespite the similarity in serum and transudative PWD fluid in terms of biochemical content, we found that when we carried out further proteomic analysis, PWD contains lymph-specific proteins. Unlike PWD, these proteins were not determined in serum. PWD fluid can be also called as lymphorrhea. PWD fluid with abundant proteins may also provide an appropriate environment for the growth of microorganisms.     

Application of metagenomic next-generation sequencing for suspected infected pancreatic necrosis

BackgroundMetagenomic next-generation sequencing (mNGS) is increasingly used for the clinical diagnosis of infectious diseases, but there is a paucity of data regarding the application of mNGS in the early diagnosis of infected pancreatic necrosis (IPN).ObjectiveTo investigate the clinical application value of mNGS in the pathogenic diagnosis of IPN.MethodsForty-two patients with suspected IPN were prospectively and consecutively enrolled from August 2019 to August 2021. Blood samples were collected for mNGS and microbial culture simultaneously during fever (T ≥ 38.5 °C). For patients who had indications of surgical interventions, peri-pancreatic specimens were collected for mNGS and microbial culture simultaneously during the first surgical intervention to confirm IPN. The clinical performance of mNGS and microbial culture were compared.ResultsA total of 21 patients (50.0%) were confirmed to have IPN during hospitalization. The sensitivity of blood mNGS was significantly higher than blood culture (95.2% vs. 23.8%, P < 0.001) in diagnosing IPN. The negative predictive value of blood mNGS was 90.0%. The turnaround time of mNGS was significantly shorter than that of microbial culture [(37.70 ± 1.44) vs. (115.23 ± 8.79) h, P < 0.01] and the average costs of mNGS accounted for 1.7% of the average total cost of hospitalization. The survival analysis demonstrates that the positive blood mNGS result was not associated with increased mortality (P = 0.119).ConclusionsWith more valuable diagnostic performance and shorter turnaround time, clinical mNGS represents a potential step forward in the early diagnosis of IPN.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Deep Phenotyping and Prediction of Long-term Cardiovascular Disease: Optimized by Machine Learning

BackgroundPrediction of cardiovascular disease (CVD) is important in clinical practice. Machine learning (ML) may offer an improved alternative to current CVD risk stratification in individual patients. We aim to identify important predictors and compare ML models with traditional models according to their prediction performance in a large long-term follow-up cohort.MethodsThe Atherosclerosis Risk in Communities (ARIC) study was designed to study the progression of subclinical disease to cardiovascular events over a 25-year follow-up period. All phenotypic variables at visit 1 were obtained. All-cause death, CVD, and coronary heart disease were the outcomes for analysis. The ML framework involved variable selection using the random survival forest (RSF) method, model building, and 5-fold cross-validation. Model performance was evaluated by discrimination using the Harrell concordance index (C-index), accuracy using the Brier score (BS), and interpretability using the number of variables in the model.ResultsOf the 14,842 participants in ARIC, the average age was 54.2 years, with 45.2% male and 26.2% Black participants. Thirty-eight unique variables were selected in the RSF top 20 importance ranking of all 6 outcomes. Aging, hypertension, glucose metabolism, renal function, coagulation, adiposity, and sodium retention dominated the predictions of all outcomes. The ML models outperformed the regression models and established risk scores with a higher C-index, lower BS, and varied interpretability.ConclusionsThe ML framework is useful for identifying important predictors of CVD and for developing models with robust performance compared with existing risk models.     

Potentilla anserine L. polysaccharide protects against cadmium-induced neurotoxicity

Cadmium is a toxic metal that can damage the brain and other organs. This study aimed to explore the protective effects of Potentilla anserine L. polysaccharide (PAP) against CdCl₂-induced neurotoxicity in N2a and SH-SY5Y cells and in the cerebral cortex of BALB/c mice. In addition, we aimed to identify the potential mechanisms underlying these protective effects. Relative to CdCl₂ treatment alone, pretreatment with PAP prevented the reduction in cell viability evoked by CdCl₂, decreased rates of apoptosis, promoted calcium homeostasis, decreased ROS accumulation, increased mitochondrial membrane potential, inhibited cytochrome C and AIF release, and prevented the cleavage of caspase-3 and PARP. In addition, PAP significantly decreased the CdCl₂-induced phosphorylation of CaMKII, Akt, and mTOR. In conclusion, PAP represents a potential therapeutic agent for the treatment of Cd-induced neurotoxicity, functioning in part via attenuating the activation of the mitochondrial apoptosis pathway and the Ca²⁺-CaMKII-dependent Akt/mTOR pathway.     

Attitude toward a mandatory COVID-19 vaccination policy and its determinants: Evidence from serial cross-sectional surveys conducted throughout the pandemic in Germany

BackgroundMandating vaccination against COVID-19 is often discussed as a means to counter low vaccine uptake. Beyond the potential legal, ethical, and psychological concerns, a successful implementation also needs to consider citizens’ support for such a policy. Public attitudes toward vaccination mandates and their determinants might differ over time and, hence, should be monitored.MethodsBetween April 2020 and April 2021, we investigated public support for mandatory vaccination policies in Germany and examined individual correlates, such as vaccination intentions, confidence in vaccine safety, and perceived collective responsibility, using a series of cross-sectional, quota-representative surveys (overall N = 27,509).ResultsSupport for a vaccination mandate declined before the approval of the first vaccine against COVID-19 in December 2020 and increased afterwards. However, at the end of April 2021, only half of respondents were in favor of mandatory regulations. In general, mandates were endorsed by those who considered the vaccines to be safe, anticipated practical barriers, and felt responsible for the collective. On the contrary, perceiving vaccination as unnecessary and weighing the benefits and risks of vaccination was related to lower support. Older individuals and males more often endorsed vaccination mandates than did younger participants and females. Interestingly, there was a gap between vaccination intentions and support for mandates, showing that the attitude toward mandatory vaccination was not only determined by vaccination-related factors such as vaccine safety or prosocial considerations.ConclusionsBecause of low public support, mandatory vaccination against COVID-19 should be considered a measure of last resort in Germany. However, if removing barriers to vaccination and educational campaigns about vaccine safety and the societal benefits of high vaccination uptake are not sufficient for increasing vaccination uptake to the required levels, mandates could be introduced. In this case, measures to ensure and increase acceptance and adherence should be taken.