Air- and Dust-Borne Fungi in Indoor and Outdoor Home of Allergic Patients in a Dust-Storm-Affected Area

Despite the recent increases in fungi-induced allergic diseases, there is no report yet in the region of the Persian Gulf on concentration levels of fungi in relationship with health state. Therefore, our aim was to measure fungi prevalence as well as to evaluate the relationships between air- and dust-borne fungal genera and allergic diseases. A matched case-control study was carried out including 45 allergic cases and 45 age- and gender-matched controls for each individual. Indoor and outdoor dust and indoor air samples were collected from participant homes during May to October 2015. A Quick Take 30 Pump and sterile wet swab were used to determine fungal types and their amounts in the air (CFU/m³) and dust (CFU/100 cm²) samples, respectively. A significant reverse association was found between indoor dust-borne Alternaria and asthma (Odds ratio (OR) = 0.14, 95% CI = 0.02–0.86). Contrarily, increased levels of indoor air-borne Aspegillus fumigatus (OR = 2.00, 95% CI = 0.37–10.55) and Alternaria (OR = 3.00, 95% CI = 0.34–25.83) were correlated with asthma development. Also, correlation analysis showed a significant relation between indoor air-borne Penicillium levels and reactivity to skin prick test in asthmatic patients (p = 0.04). Our findings support the notion that fungal exposures can either cause or prevent the development of allergic diseases. Accordingly, appropriate measures should be taken for a better management of fungi-induced allergic diseases.     

The protective effect of berberine against lipopolysaccharide-induced abortion by modulation of inflammatory/immune responses

Objective: Berberine is an isoquinoline derivative alkaloid with anti-inflammatory activity. In this study, we investigated the protective effects of berberine in prevention of LPS-induced abortion.

Materials and methods: On the gestation day (GD) 9.5, the pregnant mice were injected with low, medium, and high doses of berberine or with PBS. After 4?h, berberine or PBS-pretreated mice were injected with LPS. On GD 11.5, blood samples and uterine tissues were collected from treated mice and percentage of abortion and serum levels of NO, TNF-α, IL-10, and IL12p70 were measured by macroscopic examination and sandwich ELISA, respectively.

Results: Our findings show that mice injected with berberine were resistant to LPS-induced abortion. We also found that this treatment prevents the reduction of IL-10 and the enhancement of NO, TNF-α, and IL-12p70 in LPS-treated pregnant mice.

Conclusions: Taken together, our results suggest that berberine as an anti-inflammatory agent has protective effects on LPS-induced abortion by modulation of inflammatory/immune responses.     

KIR2DS1, 2DS5, 3DS1 and KIR2DL5 are associated with the risk of head and neck squamous cell carcinoma in Iranians

Background

Activating and inhibitory KIR receptors (aKIR, iKIR) control the development and function of NK cells whose function alterations adjust the tumor microenvironment immunity. This research was conducted to determine the KIRs gene impact on genetic predisposition to Head and Neck Squamous Cell Carcinoma (HNSCC) in Iranians.

Natural language processing to identify social determinants of health in Alzheimer's disease and related dementia from electronic health records

Objective

To develop a natural language processing (NLP) algorithm that identifies social determinants of health (SDoH), including housing, transportation, food, and medication insecurities, social isolation, abuse, neglect, or exploitation, and financial difficulties for patients with Alzheimer's disease and related dementias (ADRD) from unstructured electronic health records (EHRs).

Data Sources and Study Setting

We leveraged 1000 medical notes randomly selected from 7401 emergency department and inpatient social worker notes generated between 2015 and 2019 for 231 unique patients diagnosed with ADRD at Michigan Medicine.

Study Design

We developed a rule-based NLP algorithm for the identification of seven domains of SDoH noted above. We also compared the rule-based algorithm with deep learning and regularized logistic regression approaches. These models were compared using accuracy, sensitivity, specificity, F1 score, and the area under the receiver operating characteristic curve (AUC). All notes were split into 700 notes for training NLP algorithms, and 300 notes for validation.

Data Collection/Extraction Methods

Social worker notes used in this study were extracted from the Michigan Medicine EHR database.

Principal Findings

Of the 700 notes for training, F1 and AUC for the rule-based algorithm were at least 0.94 and 0.95, respectively, for all SDoH categories. Of the 300 notes for validation, F1 and AUC were at least 0.80 and 0.97, respectively, for all SDoH except housing and medication insecurities. The deep learning and regularized logistic regression algorithms had unsatisfactory performance.

Conclusions

The rule-based algorithm can accurately extract SDoH information in all seven domains of SDoH except housing and medication insecurities. Findings from the algorithm can be used by clinicians and social workers to proactively address social needs of patients with ADRD and other vulnerable patient populations.     

Stachys schtschegleevii tea,matrix metalloproteinase,and disease severity in female rheumatoid arthritis patients: a randomized controlled clinical trial

Clinical Rheumatology - Stachys schtschegleevii (SSC) is a herbal medicine used to treat infections. To date, this is the first study aimed to investigate the effects of SSC tea on disease activity...