Meta-Analysis of the Efficacy of Raman Spectroscopy and Machine-Learning-Based Identification of Glioma Tissue.

Intraoperative Raman spectroscopy (RS) has been identified as a potential tool for surgeons to rapidly and noninvasively differentiate between diseased and normal tissue. Since the previous meta-analysis on the subject was published in 2016, improvements in both spectroscopy equipment and machine learning models used to process spectra may have led to an increase in RS efficacy. Therefore, we decided to conduct a meta-analysis to determine the efficacy of RS when differentiating between glioma tissue and normal brain tissue. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed while conducting this meta-analysis. A search was conducted on PubMed and Web of Science for prospective and retrospective studies published between 2016 and 2022 using intraoperative RS and standard histology methods to differentiate between glioma and normal brain tissue. Meta-analyses of log odds ratios, sensitivity, and specificity were conducted in JASP using the random-effects model with restricted maximum likelihood estimation. A total of 9 studies met our inclusion criteria, comprising 673 patients and 8319 Raman spectra. Meta-analysis of log diagnostic odds ratios revealed high heterogeneity (I2 = 79.83%) and yielded a back-transformed diagnostic odds ratio of 76.71 (95% confidence interval: 39.57-148.71). Finally, meta-analysis for sensitivity and specificity of RS for glioma tissue showed high heterogeneity (I2 = 99.37% and 98.21%, respectively) and yielded an overall sensitivity of 95.3% (95% confidence interval: 91.0%-99.6%) and an overall specificity of 71.2% (95% confidence interval: 54.8%-87.6%). Calculation of a summary receiver operating curve yielded an overall area under the curve of 0.9265. Raman spectroscopy represents a promising tool for surgeons to quickly and accurately differentiate between healthy brain tissue and glioma tissue.

Elucidation of sex from mature Palmer amaranth (Amaranthus palmeri) leaves using a portable Raman spectrometer.

Palmer amaranth (Amaranthus palmeri) is a pervasive and troublesome weed species that poses significant challenges to agriculture in the United States. Identifying the sex of Palmer amaranth plants is crucial for developing tailored control measures due to the distinct characteristics and reproductive strategies exhibited by male and female plants. Traditional methods for sex determination are expensive and time-consuming, but recent advancements in spectroscopic techniques offer new possibilities. This study explores the potential of portable Raman spectroscopy for determining the sex of mature Palmer amaranth plants in-field. Raman analysis of the plant leaves reveals spectral differences associated with nitrate salts, lipids, carotenoids, and terpenoids, allowing for high accuracy and reliable identification of the plant's sex; male plants had higher concentrations of these compounds compared to females. It was also found that male plants had higher concentrations of these compounds compared to the females. Raman spectra were analyzed using a machine learning tool, partial least squares discriminant analysis (PLS-DA), to generate accuracies of no less than 83.7% when elucidating sex from acquired spectra. These findings provide insights into the sex-specific characteristics of Palmer amaranth and suggest that Raman analysis, combined with PLS-DA, can be a promising, non-destructive, and efficient method for sex determination in field settings. This approach has implications for developing sex-specific management strategies to monitor and control this invasive weed in real-world environments, benefiting farmers, agronomists, researchers, and master gardeners.

Systematic Review of Molecular Targeted Therapies for Adult-Type Diffuse Glioma: An Analysis of Clinical and Laboratory Studies.

Gliomas are the most common brain tumor in adults, and molecularly targeted therapies to treat gliomas are becoming a frequent topic of investigation. The current state of molecular targeted therapy research for adult-type diffuse gliomas has yet to be characterized, particularly following the 2021 WHO guideline changes for classifying gliomas using molecular subtypes. This systematic review sought to characterize the current state of molecular target therapy research for adult-type diffuse glioma to better inform scientific progress and guide next steps in this field of study. A systematic review was conducted in accordance with PRISMA guidelines. Studies meeting inclusion criteria were queried for study design, subject (patients, human cell lines, mice, etc.), type of tumor studied, molecular target, respective molecular pathway, and details pertaining to the molecular targeted therapy-namely the modality, dose, and duration of treatment. A total of 350 studies met the inclusion criteria. A total of 52 of these were clinical studies, 190 were laboratory studies investigating existing molecular therapies, and 108 were laboratory studies investigating new molecular targets. Further, a total of 119 ongoing clinical trials are also underway, per a detailed query on clinicaltrials.gov. GBM was the predominant tumor studied in both ongoing and published clinical studies as well as in laboratory analyses. A few studies mentioned IDH-mutant astrocytomas or oligodendrogliomas. The most common molecular targets in published clinical studies and clinical trials were protein kinase pathways, followed by microenvironmental targets, immunotherapy, and cell cycle/apoptosis pathways. The most common molecular targets in laboratory studies were also protein kinase pathways; however, cell cycle/apoptosis pathways were the next most frequent target, followed by microenvironmental targets, then immunotherapy pathways, with the wnt/ß-catenin pathway arising in the cohort of novel targets. In this systematic review, we examined the current evidence on molecular targeted therapy for adult-type diffuse glioma and discussed its implications for clinical practice and future research. Ultimately, published research falls broadly into three categories-clinical studies, laboratory testing of existing therapies, and laboratory identification of novel targets-and heavily centers on GBM rather than IDH-mutant astrocytoma or oligodendroglioma. Ongoing clinical trials are numerous in this area of research as well and follow a similar pattern in tumor type and targeted pathways as published clinical studies. The most common molecular targets in all study types were protein kinase pathways. Microenvironmental targets were more numerous in clinical studies, whereas cell cycle/apoptosis were more numerous in laboratory studies. Immunotherapy pathways are on the rise in all study types, and the wnt/ß-catenin pathway is increasingly identified as a novel target.

Meta-analysis on the Effectiveness of ECG Screening for Conditions Related to Sudden Cardiac Death in Young Athletes.

Controversy exists over the use of electrocardiograms (ECGs) in sports pre-participation screening. We performed a meta-analysis comparing the effectiveness of history and physical examination (H&P) with ECG at detecting both cardiac disease and sudden cardiac death-associated conditions (SCD-AC). Pre-participation studies published from 2015 to 2020 with athletes 10 to 35 years old were included. This yielded 28 011 athletes screened and 124 cardiac diagnoses, 103 of which were SCD-AC. A meta-analysis of log odds ratios (ORs) was conducted using a random-effects model. The ORs for the association between H&P and detecting both cardiac disease and SCD-AC were not statistically significant (OR = 3.4, P = .076; OR = 2.9, P = .078). The ORs for the association between ECG and detecting both cardiac disease and SCD-AC were statistically significant (60, P < .001; 148, P < .0001). In conclusion, the odds of detecting both cardiac disease and conditions related to SCD with ECG are greater than with H&P during sports pre-participation screening.

Testing Raman spectroscopy as a diagnostic approach for Lyme disease patients.

Lyme disease (LD), the leading tick-borne disease in the Northern hemisphere, is caused by spirochetes of several genospecies of the Borreliella burgdorferi sensu lato complex. LD is a multi-systemic and highly debilitating illness that is notoriously challenging to diagnose. The main drawbacks of the two-tiered serology, the only approved diagnostic test in the United States, include poor sensitivity, background seropositivity, and cross-reactivity. Recently, Raman spectroscopy (RS) was examined for its LD diagnostic utility by our earlier proof-of-concept study. The previous investigation analyzed the blood from mice that were infected with 297 and B31 strains of Borreliella burgdorferi sensu stricto (s.s.). The selected strains represented two out of the three major clades of B. burgdorferi s.s. isolates found in the United States. The obtained results were encouraging and prompted us to further investigate the RS diagnostic capacity for LD in this study. The present investigation has analyzed blood of mice infected with European genospecies, Borreliella afzelii or Borreliella garinii, or B. burgdorferi N40, a strain of the third major class of B. burgdorferi s.s. in the United States. Moreover, 90 human serum samples that originated from LD-confirmed, LD-negative, and LD-probable human patients were also analyzed by RS. The overall results demonstrated that blood samples from Borreliella-infected mice were identified with 96% accuracy, 94% sensitivity, and 100% specificity. Furthermore, human blood samples were analyzed with 88% accuracy, 85% sensitivity, and 90% specificity. Together, the current data indicate that RS should be further explored as a potential diagnostic test for LD patients.

Non-Invasive and Confirmatory Differentiation of Hermaphrodite from Both Male and Female Cannabis Plants Using a Hand-Held Raman Spectrometer.

Cannabis (Cannabis sativa L.) is a dioecious plant that produces both male and female inflorescences. In nature, male and female plants can be found with nearly equal frequency, which determines species out-crossing. In cannabis farming, only female plants are preferred due to their high yield of cannabinoids. In addition to unfavorable male plants, commercial production of cannabis faces the appearance of hermaphroditic inflorescences, species displaying both pistillate flowers and anthers. Such plants can out-cross female plants, simultaneously producing undesired seeds. The problem of hermaphroditic cannabis triggered a search for analytical tools that can be used for their rapid detection and identification. In this study, we investigate the potential of Raman spectroscopy (RS), an emerging sensing technique that can be used to probe plant biochemistry. Our results show that the biochemistry of male, female and hermaphroditic cannabis plants is drastically different which allows for their confirmatory identification using a hand-held Raman spectrometer. Furthermore, the coupling of machine learning approaches enables the identification of hermaphrodites with 98.7% accuracy, whereas both male and female plants can be identified with 100% accuracy. Considering the label-free, non-invasive and non-destructive nature of RS, the developed optical sensing approach can transform cannabis farming in the U.S. and overseas.

Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Aluminum and Iron Toxicities in Rice.

Metal toxicities can be detrimental to a plant health, as well as to the health of animals and humans that consume such plants. Metal content of plants can be analyzed using colorimetric, atomic absorption- or mass spectroscopy-based methods. However, these techniques are destructive, costly and laborious. In the current study, we investigate the potential of Raman spectroscopy (RS), a modern spectroscopic technique, for detection and identification of metal toxicities in rice. We modeled medium and high levels of iron and aluminum toxicities in hydroponically grown plants. Spectroscopic analyses of their leaves showed that both iron and aluminum toxicities can be detected and identified with ∼100% accuracy as early as day 2 after the stress initiation. We also showed that diagnostics accuracy was very high not only on early, but also on middle (day 4-day 8) and late (day 10-day 14) stages of the stress development. Importantly this approach only requires an acquisition time of 1 s; it is non-invasive and non-destructive to plants. Our findings suggest that if implemented in farming, RS can enable pre-symptomatic detection and identification of metallic toxins that would lead to faster recovery of crops and prevent further damage.