In Vitro Cytotoxicity of Antiresorptive and Antiangiogenic Compounds on Oral Tissues Contributing to MRONJ: Systematic Review

Background: Invasive dental treatment in patients exposed to antiresorptive and antiangiogenic drugs can cause medication-related osteonecrosis of the jaw (MRONJ). Currently, the exact pathogenesis of this disease is unclear. Methods: In March 2022, Medline (Ovid), Embase (Ovid), Scopus, and Web of Science were screened to identify eligible in vitro studies investigating the effects of antiresorptive and antiangiogenic compounds on orally derived cells. Results: Fifty-nine articles met the inclusion criteria. Bisphosphonates were used in 57 studies, denosumab in two, and sunitinib and bevacizumab in one. Zoledronate was the most commonly used nitrogen-containing bisphosphonate. The only non-nitrogen-containing bisphosphonate studied was clodronate. The most frequently tested tissues were gingival fibroblasts, oral keratinocytes, and alveolar osteoblasts. These drugs caused a decrease in cell proliferation, viability, and migration. Conclusions: Antiresorptive and antiangiogenic drugs displayed cytotoxic effects in a dose and time-dependent manner. Additional research is required to further elucidate the pathways of MRONJ

Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders

Accurately quantifying errors in soil moisture measurements from in situ sensors at fixed locations is essential for reliable state and parameter estimation in probabilistic soil hydrological modeling. This quantification becomes particularly challenging when the number of sensors per field or measurement zone (MZ) is limited. When direct calculation of errors from sensor data in a certain MZ is not feasible, we propose to pool systematic and random errors of soil moisture measurements for a specific measurement setup and derive a pooled error covariance matrix that applies to this setup across different fields and soil types. In this study, a pooled error covariance matrix was derived using soil moisture sensor measurements from three TEROS 10 (Meter Group, Inc., USA) sensors per MZ and soil moisture sampling campaigns conducted over three growing seasons, covering 93 cropping cycles in agricultural fields with diverse soil textures in Belgium. The MZ soil moisture estimated from a composite of nine soil samples with a small standard error (0.0038 m3 m−3) was considered the “true” MZ soil moisture. Based on these measurement data, we established a pooled linear recalibration of the TEROS 10 manufacturer's sensor calibration function. Then, for each individual sensor as well as for each MZ, we identified systematic offsets and temporally varying residual deviations between the calibrated sensor data and sampling data. Sensor deviations from the “true” MZ soil moisture were defined as observational errors and lump both measurement errors and representational errors. Since a systematic offset persists over time, it contributes to the temporal covariance of sensor observational errors. Therefore, we estimated the temporal covariance of observational errors of the individual and the MZ-averaged sensor measurements from the variance of the systematic offsets across all sensors and MZ averages, while the random error variance was derived from the variance of the pooled residual deviations. The total error variance was then obtained as the sum of these two components. Due to spatial soil moisture correlation, the variance and temporal covariance of MZ-averaged sensor observational errors could not be derived accurately from the individual sensor error variances and temporal covariances, assuming that the individual observational errors of the three sensors in a MZ were not correlated with each other. The pooled error covariance matrix of the MZ-averaged soil moisture measurements indicated a significant autocorrelation of sensor observational errors of 0.518, as the systematic error standard deviation (σα‾= 0.033 m3 m−3) was similar to the random error standard deviation (σϵ‾= 0.032 m3 m−3). To illustrate the impact of error covariance in probabilistic soil hydrological modeling, a case study was presented incorporating the pooled error covariance matrix in a Bayesian inverse modeling framework. These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. Further research is required to assess to what extent the error covariances found in this study can be transferred to other areas and how they impact parameter estimation in soil hydrological modeling.</p

The Potential of Modified and Multimeric Antimicrobial Peptide Materials as Superbug Killers

Antimicrobial peptides (AMPs) are found in nearly all living organisms, show broad spectrum antibacterial activity, and can modulate the immune system. Furthermore, they have a very low level of resistance induction in bacteria, which makes them an ideal target for drug development and for targeting multi-drug resistant bacteria 'Superbugs'. Despite this promise, AMP therapeutic use is hampered as typically they are toxic to mammalian cells, less active under physiological conditions and are susceptible to proteolytic degradation. Research has focused on addressing these limitations by modifying natural AMP sequences by including e.g., d-amino acids and N-terminal and amino acid side chain modifications to alter structure, hydrophobicity, amphipathicity, and charge of the AMP to improve antimicrobial activity and specificity and at the same time reduce mammalian cell toxicity. Recently, multimerisation (dimers, oligomer conjugates, dendrimers, polymers and self-assembly) of natural and modified AMPs has further been used to address these limitations and has created compounds that have improved activity and biocompatibility compared to their linear counterparts. This review investigates how modifying and multimerising AMPs impacts their activity against bacteria in planktonic and biofilm states of growth

Human platelet lysate to substitute fetal bovine serum in hMSC expansion for translational applications: a systematic review

Foetal bovine serum (FBS), is the most commonly used culture medium additive for in vitro cultures, despite its undefined composition, its potential immunogenicity and possible prion/zoonotic transmission. For these reasons, significant efforts have been targeted at finding a substitute, such as serum free-media or human platelet-lysates (hPL). Our aim is to critically appraise the state-of-art for hPL in the published literature, comparing its impact with FBS. In June 2019 a systematic search of the entire Web of Science, Medline and PubMed database was performed with the following search terms: (mesenchymal stem cells) AND (fetal bovine serum OR fetal bovine calf) AND (human platelet lysate). Excluded from this search were review articles that were published before 2005, manuscripts in which mesenchymal stem cells (MSCs) were not from human sources, and when the FBS controls were missing. Based on our search algorithm, 56 papers were selected. A review of these papers indicated that hMSCs cultured with hPL showed a spindle-shaped elongated morphology, had higher proliferation indexes, similar cluster of differentiation (CD) markers and no significant variation in differentiation lineage (osteocyte, adipocyte, and chondrocyte) compared to those cultured with FBS. Main sources of primary hMSCs were either fat tissue or bone marrow; in a few studies cells isolated from alternative sources showed no relevant difference in their response. Despite the difference in medium choice and a lack of standardization of hPL manufacturing, the majority of publications support that hPL was at least as effective as FBS in promoting adhesion, survival and proliferation of hMSCs. We conclude that hPL should be considered a viable alternative to FBS in hMSCs culture-especially with a view for their clinical use