Autoimmune diabetes from pembrolizumab: A case report and review of literature.

BACKGROUND: Immunotherapy, specifically the use of checkpoint inhibitors such as pembrolizumab, has become an important tool in personalized cancer therapy. These inhibitors target proteins on T-cells that regulate the immune response against tumor cells. Pembrolizumab, which targets the programmed cell death 1 receptor on T-cells, has been approved for the treatment of metastatic melanoma and non-small cell lung cancer. However, it can also lead to immune-related side effects, including pneumonitis, colitis, thyroid abnormalities, and rare cases of type 1 diabetes. CASE SUMMARY: The case presented involves an adult patient in 30s with breast cancer who developed hyperglycemia after receiving pembrolizumab treatment. The patient was diagnosed with diabetic ketoacidosis and further investigations were performed to evaluate for new-onset type 1 diabetes. The patient had a history of hypothyroidism and a family history of breast cancer. Treatment for diabetic ketoacidosis was initiated, and the patient was discharged for close follow-up with an endocrinologist. CONCLUSION: This literature review highlights the occurrence of diabetic ketoacidosis and new-onset type 1 diabetes in patients receiving pembrolizumab treatment for different types of cancer. Overall, the article emphasizes the therapeutic benefits of immunotherapy in cancer treatment, particularly pembrolizumab, while also highlighting the potential side effect of immune-related diabetes that can occur in a small percentage of patients. Here we present a case where pembrolizumab lead to development of diabetes after a few cycles highlighting one of the rare yet a serious toxicity of the drug.

Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal.

According to the 2019 National Survey on Drug Use and Health, 14.5 million people ages 12 and older had alcohol abuse disorder. Alcohol withdrawal syndrome (AWS) can be defined as a collection of physical symptoms experienced due to abrupt cessation of alcohol after long-term dependence. In instances where regular inpatient management fails to control AWS symptoms, patients are shifted to intensive care units (ICUs) for closer monitoring and prevention of life-threatening complications like withdrawal seizures and delirium tremens (DTs), labeled as severe alcohol withdrawal syndrome (SAWS). Although this represents a significant healthcare burden, minimal studies have been conducted to determine objective predictors. In this study, we aim to determine the effect of patient demographics, socio-economic status, biochemical parameters, and clinical factors on the need for escalation to ICU level of care among admissions for AWS. Our study showed that factors such as a history of DTs or alcohol-related seizures, the initial protocol of management, degree of reported alcohol usage, activation of rapid response teams, mean corpuscular value, alcohol level on admission, highest Clinical Institute Withdrawal Assessment Alcohol Revised (CIWA-Ar) scored during the hospital stay, and the total amount of sedatives used were significantly associated with escalation to ICU level of care. Clinicians must use these objective parameters to identify high-risk patients and intervene early. We encourage further studies to establish a scoring algorithm incorporating biochemical parameters to tailor management algorithms that might better suit high-risk patients.

Naphthyridine derived colorimetric and fluorescent turn off sensors for Ni2+ in aqueous media.

Highly selective and sensitive 2,7-naphthyridine based colorimetric and fluorescence "Turn Off" chemosensors (L1-L4) for detection of Ni2+ in aqueous media are reported. The receptors (L1-L4) showed a distinct color change from yellow to red by addition of Ni2+ with spectral changes in bands at 535-550 nm. The changes are reversible and pH independent. The detection limits for Ni2+ by (L1-L4) are in the range of 0.2-0.5 µM by UV-Visible data and 0.040-0.47 µM by fluorescence data, which is lower than the permissible value of Ni2+ (1.2 µM) in drinking water defined by EPA. The binding stoichiometries of L1-L4 for Ni2+ were found to be 2:1 through Job's plot and ESI-MS analysis. Moreover the receptors can be used to quantify Ni2+ in real water samples. Formation of test strips by the dip-stick method increases the practical applicability of the Ni2+ test for "in-the-field" measurements. DFT calculations and AIM analyses supported the experimentally determined 2:1 stoichiometries of complexation. TD-DFT calculations were performed which showed slightly decreased FMO energy gaps due to ligand-metal charge transfer (LMCT).

A Meta-analysis of Mortality, Need for ICU admission, Use of Mechanical Ventilation and Adverse Effects with Ivermectin Use in COVID-19 Patients

ImportanceRepurposing Ivermectin, a known anti-parasitic agent, for treating COVID-19 has demonstrated positive results in several studies. We aim to evaluate the benefit and risk of Ivermectin in COVID-19. MethodsWe conducted a systematic search for full-text manuscripts published from February 1, 2020, to August 15th, 2021 focusing on Ivermectin therapy against COVID-19. The primary outcomes were mortality, need for intensive care unit (ICU) admission; secondary outcomes were - adverse effects, need for mechanical ventilation, viral clearance, time to viral clearance, need for hospitalization, and length of hospital stay. Random-effects models were used for all analyses. ResultsWe included a total of 52 studies (n=17561) in the qualitative analysis, out of these, 44 studies (n=14019) were included in the meta-analysis. In the mortality meta-analysis (N=29), odds of death were lower in the Ivermectin-arm compared to control (OR 0.54, p=0.009). Although lower odds of mortality were observed in various subgroup analyses of RCTs, they did not reach statistical significance: therapeutic RCTs: mild-moderate COVID-19 (OR 0.31, p=0.06), therapeutic RCTs: severe/critical COVID-19 (OR 0.86, p=0.56), inpatient RCTs: mild-moderate COVID-19 (OR 0.18, p=0.08), inpatient RCTs: severe/critical COVID-19 (OR 0.86, p=0.56). Ivermectin, mostly as adjuvant therapy, was associated with higher odds of viral clearance (N=22) (OR 3.52, p=0.0002), shorter duration to achieve viral clearance (N=8) (MD - 4.12, p=0.02), reduced need for hospitalization (N=6) (OR 0.34, p=008). ConclusionOur meta-analysis suggests that the mortality benefit of Ivermectin in COVID-19 is uncertain. But as adjuvant therapy, Ivermectin may improve viral clearance and reduce the need for hospitalization. HighlightsO_ST_ABSWhat We Already Know about This TopicC_ST_ABSO_LICOVID-19 is an ongoing global pandemic, for which Ivermectin has been tried on a therapeutic and prophylactic basis. C_LIO_LIResults from several clinical trials and observational studies suggest that Ivermectin may improve survival and clinical outcomes with a good safety profile when compared with other treatments; however, the current evidence is limited.. C_LI What This Article Tells Us That Is NewO_LIThis systematic review and meta-analysis provide a summary of the latest literature on the efficacy and safety of Ivermectin use for COVID-19. C_LIO_LIBased on our analysis of the latest evidence, we found that Ivermectins benefit in reducing mortality cannot be concluded with confidence. However, as an adjuvant therapy it may help reduce the need for hospitalization, duration for viral clearance while increasing the likelihood of achieving viral clearance. C_LIO_LIWe need more high-quality data for conclusive evidence regarding the benefit of Ivermectin in reducing the need for ICU admissions, mechanical ventilation and duration of hospital stay in COVID-19 patients. C_LI

MitProt-Pred: Predicting mitochondrial proteins of Plasmodium falciparum parasite using diverse physiochemical properties and ensemble classification.

Mitochondrial protein of Plasmodium falciparum is an important target for anti-malarial drugs. Experimental approaches for detecting mitochondrial proteins are costly and time consuming. Therefore, MitProt-Pred is developed that utilizes Bi-profile Bayes, Pseudo Average Chemical Shift, Split Amino Acid Composition, and Pseudo Amino Acid Composition based features of the protein sequences. Hybrid feature space is also developed by combining different individual feature spaces. These feature spaces are learned and exploited through SVM based ensemble. MitProt-Pred achieved significantly improved prediction performance for two standard datasets. We also developed the score level ensemble, which outperforms the feature level ensemble.

Predicting G-protein-coupled receptors families using different physiochemical properties and pseudo amino acid composition.

G-protein-coupled receptors (GPCRs) initiate signaling pathways via trimetric guanine nucleotide-binding proteins. GPCRs are classified based on their ligand-binding properties and molecular phylogenetic analyses. Nonetheless, these later analyses are in most case dependent on multiple sequence alignments, themselves dependent on human intervention and expertise. Alignment-free classifications of GPCR sequences, in addition to being unbiased, present many applications uncovering hidden physicochemical parameters shared among specific groups of receptors, to being used in automated workflows for large-scale molecular modeling applications. Current alignment-free classification methods, however, do not reach a full accuracy. This chapter discusses how GPCRs amino acid sequences can be classified using pseudo amino acid composition and multiscale energy representation of different physiochemical properties of amino acids. A hybrid feature extraction strategy is shown to be suitable to represent GPCRs and to be able to exploit GPCR amino acid sequence discrimination capability in spatial as well as transform domain. Classification strategies such as support vector machine and probabilistic neural network are then discussed in regards to GPCRs classification. The work of GPCR-Hybrid web predictor is also discussed.