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Fulltext Identifying Mucormycosis Severity in Indian COVID-19 Patients: A Nano-Based Diagnosis and the Necessity for Critical Therapeutic Intervention

Asdaq SMB, Rajan A, Damodaran A, Kamath SR, Nair KS, Zachariah SM, et al.

Antibiotics (Basel), 2021 Oct 27;10(11).
PMID: 34827246 DOI: 10.3390/antibiotics10111308

The COVID-19 infection caused by the new SARS-CoV-2 virus has been linked to a broad spectrum of symptoms, from a mild cough to life-threatening pneumonia. As we learn more about this unusual COVID-19 epidemic, new issues are emerging and being reported daily. Mucormycosis, also known as zygomycosis or phycomycosis, causes severe fungal illness to individuals with a weakened immune system. It is a devastating fungal infection, and the most frequent kind is the rhino cerebral type. As a devastating second wave of COVID-19 sweeps India, doctors report several instances involving a strange illness-sometimes known as the "black fungus"-among returning and recovered COVID-19 patients. This paper analyzes the existing statistical data to address the severity of prevalence and further notes the nano-based diagnostic parameters, clinical presentations, its connection with other conditions like diabetes, hypertension, and GI disorders, and the importance of anti-fungal therapy in treating the same. Anti-fungal therapies, as well as surgical interventions, are currently used for the treatment of the disease. Proper and timely diagnosis is necessary, along with the reduction in the spread of COVID-19. From the review, it was found that timely pharmacologic interventions and early diagnosis by using a nano-based diagnostic kit can help control the disease. Additionally, this paper provides novel information about the nanotechnology approaches such as fungal detection biosensors, nucleic acids-based testing, point-of-care tests, and galactomannans detection, in the diagnosis of mucormycosis, and thereby reinforces the need for further research on the topic.
Fulltext Nanotechnology Integration for SARS-CoV-2 Diagnosis and Treatment: An Approach to Preventing Pandemic

Asdaq SMB, Ikbal AMA, Sahu RK, Bhattacharjee B, Paul T, Deka B, et al.

Nanomaterials (Basel), 2021 Jul 16;11(7).
PMID: 34361227 DOI: 10.3390/nano11071841

The SARS-CoV-2 outbreak is the COVID-19 disease, which has caused massive health devastation, prompting the World Health Organization to declare a worldwide health emergency. The corona virus infected millions of people worldwide, and many died as a result of a lack of particular medications. The current emergency necessitates extensive therapy in order to stop the spread of the coronavirus. There are various vaccinations available, but no validated COVID-19 treatments. Since its outbreak, many therapeutics have been tested, including the use of repurposed medications, nucleoside inhibitors, protease inhibitors, broad spectrum antivirals, convalescence plasma therapies, immune-modulators, and monoclonal antibodies. However, these approaches have not yielded any outcomes and are mostly used to alleviate symptoms associated with potentially fatal adverse drug reactions. Nanoparticles, on the other hand, may prove to be an effective treatment for COVID-19. They can be designed to boost the efficacy of currently available antiviral medications or to trigger a rapid immune response against COVID-19. In the last decade, there has been significant progress in nanotechnology. This review focuses on the virus's basic structure, pathogenesis, and current treatment options for COVID-19. This study addresses nanotechnology and its applications in diagnosis, prevention, treatment, and targeted vaccine delivery, laying the groundwork for a successful pandemic fight.
Cannabidiol and neurodegeneration: From molecular mechanisms to clinical benefits

Jha SK, Nelson VK, Suryadevara PR, Panda SP, Pullaiah CP, Nuli MV, et al.

Ageing Res Rev, 2024 Sep;100:102386.
PMID: 38969143 DOI: 10.1016/j.arr.2024.102386

Neurodegenerative disorders (NDs) such as Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis are severe and life-threatening conditions in which significant damage of functional neurons occurs to produce psycho-motor malfunctions. NDs are an important cause of death in the elderly population worldwide. These disorders are commonly associated with the progression of age, oxidative stress, and environmental pollutants, which are the major etiological factors. Abnormal aggregation of specific proteins such as α-synuclein, amyloid-β, huntingtin, and tau, and accumulation of the associated oligomers in neurons are the hallmark pathological features of NDs. Existing therapeutic options for NDs are only symptomatic relief and do not address root-causing factors, such as protein aggregation, oxidative stress, and neuroinflammation. Cannabidiol (CBD) is a non-psychotic natural cannabinoid obtained from Cannabis sativa that possesses multiple pharmacological actions, including antioxidant, anti-inflammatory, and neuroprotective effects in various NDs and other neurological disorders both in vitro and in vivo. CBD has gained attention as a promising drug candidate for the management of neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease, by inhibiting protein aggregation, free radicals, and neuroinflammation. In parallel, CBD has shown positive results in other neurological disorders, such as epilepsy, depression, schizophrenia, and anxiety, as well as adjuvant treatment with existing standard therapeutic agents. Hence, the present review focuses on exploring the possible molecular mechanisms in controlling various neurological disorders as well as the clinical applications of CBD in NDs including epilepsy, depression and anxiety. In this way, the current review will serve as a standalone reference for the researchers working in this area.
Fulltext Resveratrol-Based Nanoformulations as an Emerging Therapeutic Strategy for Cancer

Sharifi-Rad J, Quispe C, Mukazhanova Z, Knut E, Turgumbayeva A, Kipchakbayeva A, et al.

Front Mol Biosci, 2021;8:649395.
PMID: 34540888 DOI: 10.3389/fmolb.2021.649395

Resveratrol is a polyphenolic stilbene derivative widely present in grapes and red wine. Broadly known for its antioxidant effects, numerous studies have also indicated that it exerts anti-inflammatory and antiaging abilities and a great potential in cancer therapy. Regrettably, the oral administration of resveratrol has pharmacokinetic and physicochemical limitations such as hampering its effects so that effective administration methods are demanding to ensure its efficiency. Thus, the present review explores the published data on the application of resveratrol nanoformulations in cancer therapy, with the use of different types of nanodelivery systems. Mechanisms of action with a potential use in cancer therapy, negative effects, and the influence of resveratrol nanoformulations in different types of cancer are also highlighted. Finally, the toxicological features of nanoresveratrol are also discussed.
Fulltext Nigella Plants - Traditional Uses, Bioactive Phytoconstituents, Preclinical and Clinical Studies

Salehi B, Quispe C, Imran M, Ul-Haq I, Živković J, Abu-Reidah IM, et al.

Front Pharmacol, 2021;12:625386.
PMID: 33981219 DOI: 10.3389/fphar.2021.625386

Nigella is a small genus of the family Ranunculaceae, which includes some popular species due to their culinary and medicinal properties, especially in Eastern Europe, Middle East, Western, and Central Asia. Therefore, this review covers the traditional uses and phytochemical composition of Nigella and, in particular, Nigella sativa. The pharmacological studies reported in vitro, in vivo, and in humans have also been reviewed. One of the main strength of the use of Nigella is that the seeds are rich in the omega-6 fatty acid linoleic acid and provide an extra-source of dietary phytochemicals, including the bioactive thymoquinone, and characteristics saponins, alkaloids, and flavonoids. Among Nigella species, N. sativa L. is the most studied plant from the genus. Due to the phytochemical composition and pharmacological properties, the seed and seed oil from this plant can be considered as good candidates to formulate functional ingredients on the basis of folklore and scientific knowledge. Nonetheless, the main limations are that more studies, especially, clinical trials are required to standardize the results, e.g. to establish active molecules, dosage, chemical profile, long-term effects and impact of cooking/incorporation into foods.
Fulltext Genistein: An Integrative Overview of Its Mode of Action, Pharmacological Properties, and Health Benefits

Sharifi-Rad J, Quispe C, Imran M, Rauf A, Nadeem M, Gondal TA, et al.

Oxid Med Cell Longev, 2021;2021:3268136.
PMID: 34336089 DOI: 10.1155/2021/3268136

Genistein is an isoflavone first isolated from the brooming plant Dyer's Genista tinctoria L. and is widely distributed in the Fabaceae family. As an isoflavone, mammalian genistein exerts estrogen-like functions. Several biological effects of genistein have been reported in preclinical studies, such as the antioxidant, anti-inflammatory, antibacterial, and antiviral activities, the effects of angiogenesis and estrogen, and the pharmacological activities on diabetes and lipid metabolism. The purpose of this review is to provide up-to-date evidence of preclinical pharmacological activities with mechanisms of action, bioavailability, and clinical evidence of genistein. The literature was researched using the most important keyword "genistein" from the PubMed, Science, and Google Scholar databases, and the taxonomy was validated using The Plant List. Data were also collected from specialized books and other online resources. The main positive effects of genistein refer to the protection against cardiovascular diseases and to the decrease of the incidence of some types of cancer, especially breast cancer. Although the mechanism of protection against cancer involves several aspects of genistein metabolism, the researchers attribute this effect to the similarity between the structure of soy genistein and that of estrogen. This structural similarity allows genistein to displace estrogen from cellular receptors, thus blocking their hormonal activity. The pharmacological activities resulting from the experimental studies of this review support the traditional uses of genistein, but in the future, further investigations are needed on the efficacy, safety, and use of nanotechnologies to increase bioavailability and therapeutic efficacy.
Comparison of the accuracy of the 7-item HADS Depression subscale and 14-item total HADS for screening for major depression: A systematic review and individual participant data meta-analysis

Wu Y, Levis B, Daray FM, Ioannidis JPA, Patten SB, Cuijpers P, et al.

Psychol Assess, 2023 Feb;35(2):95-114.
PMID: 36689386 DOI: 10.1037/pas0001181

The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from -0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02-0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Fulltext The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis

He C, Levis B, Riehm KE, Saadat N, Levis AW, Azar M, et al.

Psychother Psychosom, 2020;89(1):25-37.
PMID: 31593971 DOI: 10.1159/000502294

BACKGROUND: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.
OBJECTIVE: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10.
METHODS: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview.
RESULTS: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88).
CONCLUSIONS: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.
Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale - Depression subscale scores: An individual participant data meta-analysis of 73 primary studies

Wu Y, Levis B, Sun Y, Krishnan A, He C, Riehm KE, et al.

J Psychosom Res, 2020 02;129:109892.
PMID: 31911325 DOI: 10.1016/j.jpsychores.2019.109892

OBJECTIVE: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D).
METHODS: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores.
RESULTS: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)).
CONCLUSION: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.
Fulltext Data-Driven Cutoff Selection for the Patient Health Questionnaire-9 Depression Screening Tool

Levis B, Bhandari PM, Neupane D, Fan S, Sun Y, He C, et al.

JAMA Netw Open, 2024 Nov 04;7(11):e2429630.
PMID: 39576645 DOI: 10.1001/jamanetworkopen.2024.29630

IMPORTANCE: Test accuracy studies often use small datasets to simultaneously select an optimal cutoff score that maximizes test accuracy and generate accuracy estimates.
OBJECTIVE: To evaluate the degree to which using data-driven methods to simultaneously select an optimal Patient Health Questionnaire-9 (PHQ-9) cutoff score and estimate accuracy yields (1) optimal cutoff scores that differ from the population-level optimal cutoff score and (2) biased accuracy estimates.
DESIGN, SETTING, AND PARTICIPANTS: This study used cross-sectional data from an existing individual participant data meta-analysis (IPDMA) database on PHQ-9 screening accuracy to represent a hypothetical population. Studies in the IPDMA database compared participant PHQ-9 scores with a major depression classification. From the IPDMA population, 1000 studies of 100, 200, 500, and 1000 participants each were resampled.
MAIN OUTCOMES AND MEASURES: For the full IPDMA population and each simulated study, an optimal cutoff score was selected by maximizing the Youden index. Accuracy estimates for optimal cutoff scores in simulated studies were compared with accuracy in the full population.
RESULTS: The IPDMA database included 100 primary studies with 44 503 participants (4541 [10%] cases of major depression). The population-level optimal cutoff score was 8 or higher. Optimal cutoff scores in simulated studies ranged from 2 or higher to 21 or higher in samples of 100 participants and 5 or higher to 11 or higher in samples of 1000 participants. The percentage of simulated studies that identified the true optimal cutoff score of 8 or higher was 17% for samples of 100 participants and 33% for samples of 1000 participants. Compared with estimates for a cutoff score of 8 or higher in the population, sensitivity was overestimated by 6.4 (95% CI, 5.7-7.1) percentage points in samples of 100 participants, 4.9 (95% CI, 4.3-5.5) percentage points in samples of 200 participants, 2.2 (95% CI, 1.8-2.6) percentage points in samples of 500 participants, and 1.8 (95% CI, 1.5-2.1) percentage points in samples of 1000 participants. Specificity was within 1 percentage point across sample sizes.
CONCLUSIONS AND RELEVANCE: This study of cross-sectional data found that optimal cutoff scores and accuracy estimates differed substantially from population values when data-driven methods were used to simultaneously identify an optimal cutoff score and estimate accuracy. Users of diagnostic accuracy evidence should evaluate studies of accuracy with caution and ensure that cutoff score recommendations are based on adequately powered research or well-conducted meta-analyses.

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