Kidney transplantation in multiple myeloma in 2023: A short review.

Patients with multiple myeloma (MM) frequently present with kidney involvement, of which a non-negligible proportion will progress to end-stage kidney disease. Kidney transplantation (KT) is the preferred kidney replacement therapy for selected patients; however, there are still many uncertainties regarding its application in MM patients. The risk of hematological relapse and subsequent graft loss or patient death often leads nephrologists to deem these patients unfit for KT. As such, data on KT in MM patients are heterogeneous and originate from individual case reports and small case series. Although MM is still an incurable disease, the addition of newer drugs and autologous hematopoietic stem cell transplant (HSCT) in the standard of care has been increasing patients' overall survival in recent decades. Risk stratification using cytogenetic studies and minimal residual disease detection are helpful in assessing the risk of relapse in patients who attain a complete response after HSCT. The greatest challenges remain the correct identification of patients who will most probably benefit from KT from a survival perspective and the determination of how long relapse-free survival should be before the transplant is performed.

Nerve growth factor inducible (VGF) is a secreted mediator for metastatic breast cancer tropism to the brain.

Brain metastases are one of the most serious clinical problems in breast cancer (BC) progression, associated with lower survival rates and a lack of effective therapies. Thus, to dissect the early stages of the brain metastatic process, we studied the impact of brain organotropic BC cells' secretomes on the establishment of the brain pre-metastatic niche (PMN). We found that BC cells with specific tropism to the brain caused significant blood-brain barrier (BBB) disruption, as well as microglial activation, in both in vitro and in vivo models. Further, we searched for a brain-organotropic metastatic signature, as a promising source for the discovery of new biomarkers involved in brain metastatic progression. Of relevance, we identified VGF (nerve growth factor inducible) as a key mediator in this process, also impacting the BBB and microglial functions both in vitro and in vivo. In a series of human breast tumors, VGF was found to be expressed in both cancer cells and the adjacent stroma. Importantly, VGF-positive tumors showed a significantly worse prognosis and were associated with HER2 (human epidermal growth factor receptor 2) overexpression and triple-negative molecular signatures. Further clinical validation in primary tumors from metastatic BC cases showed a significant association between VGF and the brain metastatic location, clearly and significantly impacting on the prognosis of BC patients with brain metastasis. In conclusion, our study reveals a unique secretome signature for BC with a tropism for the brain, highlighting VGF as a crucial mediator in this process. Furthermore, its specific impact as a poor prognostic predictor for BC patients with brain metastasis opens new avenues to target VGF to control the progression of brain metastatic disease. © 2024 The Pathological Society of Great Britain and Ireland.

A Magnetic Field-Based Wearable Respiration Sensor for Real-Time Monitoring During Pulmonary Rehabilitation.

OBJECTIVE: This work explores Hall effect sensing paired with a permanent magnet, in the context of pulmonary rehabilitation exercise training. METHODS: Experimental evaluation was performed considering as reference the gold-standard of respiratory monitoring, an airflow transducer, and performance was compared to another wearable device with analogous usability - a piezoelectric sensor. A total of 16 healthy participants performed 15 activities, representative of pulmonary rehabilitation exercises, simultaneously using all devices. Evaluation was performed based on detection of flow reversal events and key respiratory parameters. RESULTS: Overall, the proposed sensor outperformed the piezoelectric sensor with a mean ratio, precision, and recall of 0.97, 0.97, and 0.95, respectively, against 0.98, 0.90, and 0.88. Evaluation regarding the respiratory parameters indicates an adequate accuracy when it comes to breath cycle, inspiration, and expiration times, with mean relative errors around 4% for breath cycle and 8% for inspiration/expiration times, despite some variability. Bland-Altman analysis indicates no systematic biases. CONCLUSION: Characterization of the proposed sensor shows adequate monitoring capabilities for exercises that do not rely heavily on torso mobility, but may present a limitation when it comes to activities such as side stretches. SIGNIFICANCE: This work provides a comprehensive characterization of a magnetic field-based respiration sensor, including a discussion on its robustness to different algorithm thresholds. It proves the viability of the sensor in a range of exercises, expanding the applicability of Hall effect sensors as a feasible wearable approach to real-time respiratory monitoring.

Relationship between wintering site and survival in a migratory waterbird using different migration routes.

When wintering at different sites, individuals from the same breeding population can experience different conditions, with costs and benefits that may have implications throughout their lifetime. Using a dataset from a longitudinal study on Eurasian Spoonbills from southern France, we explored whether survival rate varied among individuals using different wintering sites. In the last 13 years, more than 3000 spoonbills have been ringed as chicks in Camargue. These birds winter in five main regions that vary in both migratory flyway (East Atlantic vs. Central European) and migration distance (long-distance vs. short-distance vs. resident). We applied Cormack-Jolly-Seber models and found evidence for apparent survival to correlate with migration distance, but not with flyway. During the interval between the first winter sighting and the next breeding period, long-distance migrants had the lowest survival, independently of the flyway taken. Additionally, as they age, spoonbills seem to better cope with migratory challenges and wintering conditions as no differences in apparent survival among wintering strategies were detected during subsequent years. As dispersal to other breeding colonies was rarely observed, the lower apparent survival during this period is likely to be partly driven by lower true survival. This supports the potential role of crossing of natural barriers and degradation of wintering sites in causing higher mortality rates as recorded for a variety of long-distance migrants. Our work confirms variation in demographic parameters across winter distribution ranges and reinforces the importance of longitudinal studies to better understand the complex demographics of migratory species.

Severe Acute Kidney Injury in Hospitalized Cancer Patients: Epidemiology and Predictive Model of Renal Replacement Therapy and In-Hospital Mortality.

BACKGROUND: Acute kidney injury (AKI) is a common complication among cancer patients, often leading to longer hospital stays, discontinuation of cancer treatment, and a poor prognosis. This study aims to provide insight into the incidence of severe AKI in this population and identify the risk factors associated with renal replacement therapy (RRT) and in-hospital mortality. METHODS: This retrospective cohort study included 3201 patients with cancer and severe AKI admitted to a Comprehensive Cancer Center between January 1995 and July 2023. Severe AKI was defined according to the KDIGO guidelines as grade ≥ 2 AKI with nephrological in-hospital follow-up. Data were analyzed in two timelines: Period A (1995-2010) and Period B (2011-2023). RESULTS: A total of 3201 patients (1% of all hospitalized cases) were included, with a mean age of 62.5 ± 17.2 years. Solid tumors represented 75% of all neoplasms, showing an increasing tendency, while hematological cancer decreased. Obstructive AKI declined, whereas the incidence of sepsis-associated, prerenal, and drug-induced AKI increased. Overall, 20% of patients required RRT, and 26.4% died during hospitalization. A predictive model for RRT (AUC 0.833 [95% CI 0.817-0.848]) identified sepsis and hematological cancer as risk factors and prerenal and obstructive AKI as protective factors. A similar model for overall in-hospital mortality (AUC 0.731 [95% CI 0.71-0.752]) revealed invasive mechanical ventilation (IMV), sepsis, and RRT as risk factors and obstructive AKI as a protective factor. The model for hemato-oncological patients' mortality (AUC 0.832 [95% CI 0.803-0.861]) included IMV, sepsis, hematopoietic stem cell transplantation, and drug-induced AKI. Mortality risk point score models were derived from these analyses. CONCLUSIONS: This study addresses the demographic and clinical features of cancer patients with severe AKI. The development of predictive models for RRT and in-hospital mortality, along with risk point scores, may play a role in the management of this population.

How does the electric field induced by tDCS influence motor-related connectivity? Model-guided perspectives.

Over the last decade, transcranial direct current stimulation (tDCS) has been applied not only to modulate local cortical activation, but also to address communication between functionally-related brain areas. Stimulation protocols based on simple two-electrode placements are being replaced by multi-electrode montages to target intra- and inter-hemispheric neural networks using multichannel/high definition paradigms.Objective. This study aims to investigate the characteristics of electric field (EF) patterns originated by tDCS experiments addressing changes in functional brain connectivity.Methods. A previous selection of tDCS experimental studies aiming to modulate motor-related connectivity in health and disease was conducted. Simulations of the EF induced in the cortex were then performed for each protocol selected. The EF magnitude and orientation are determined and analysed in motor-related cortical regions for five different head models to account for inter-subject variability. Functional connectivity outcomes obtained are qualitatively analysed at the light of the simulated EF and protocol characteristics, such as electrode position, number and stimulation dosing.Main findings. The EF magnitude and orientation predicted by computational models can be related with the ability of tDCS to modulate brain functional connectivity. Regional differences in EF distributions across subjects can inform electrode placements more susceptible to inter-subject variability in terms of brain connectivity-related outcomes.Significance. Neuronal facilitation/inhibition induced by tDCS fields may indirectly influence intra and inter-hemispheric connectivity by modulating neural components of motor-related networks. Optimization of tDCS using computational models is essential for adequate dosing delivery in specific networks related to clinically relevant connectivity outcomes.

Rational approach to design gold nanoparticles for photothermal therapy: the effect of gold salt on physicochemical, optical and biological properties.

Among the unique characteristics associated to gold nanoparticles (AuNPs) in biomedicine, their ability to convert light energy into heat opens ventures for improved cancer therapeutic options, such as photothermal therapy (PTT). PTT relies on the local hyperthermia of tumor cells upon irradiation with light beams, and the association of AuNPs with radiation within the near infrared (NIR) range constitutes an advantageous strategy to potentially improve PTT efficacy. Herein, it was explored the effect of the gold salt on the AuNPs' physicochemical and optical properties. Mostly spherical-like negatively charged AuNPs with variable sizes and absorbance spectra were obtained. In addition, photothermal features were assessed using in vitro phantom models. The best formulation showed the ability to increase their temperature in aqueous solution up to 19 °C when irradiated with a NIR laser for 20 min. Moreover, scanning transmission electron microscopy confirmed the rearrangement of the gold atoms in a face-centered cubic structure, which further allowed to calculate the photothermal conversion efficiency upon combination of theoretical and experimental data. AuNPs also showed local retention after being locally administered in in vivo models. These last results obtained by computerized tomography allow to consider these AuNPs as promising elements for a PTT system. Moreover, AuNPs showed high potential for PTT by resulting in in vitro cancer cells' viability reductions superior to 70 % once combine with 5 min of NIR irradiation.

Nucleic Acid Aptamer-Based Biosensors: A Review.

Aptamers, short strands of either DNA, RNA, or peptides, known for their exceptional specificity and high binding affinity to target molecules, are providing significant advancements in the field of health. When seamlessly integrated into biosensor platforms, aptamers give rise to aptasensors, unlocking a new dimension in point-of-care diagnostics with rapid response times and remarkable versatility. As such, this review aims to present an overview of the distinct advantages conferred by aptamers over traditional antibodies as the molecular recognition element in biosensors. Additionally, it delves into the realm of specific aptamers made for the detection of biomarkers associated with infectious diseases, cancer, cardiovascular diseases, and metabolomic and neurological disorders. The review further elucidates the varying binding assays and transducer techniques that support the development of aptasensors. Ultimately, this review discusses the current state of point-of-care diagnostics facilitated by aptasensors and underscores the immense potential of these technologies in advancing the landscape of healthcare delivery.

Studying Erythromelalgia Using Doppler Flowmetry Perfusion Signals and Wavelet Analysis-An Exploratory Study.

Erythromelalgia (EM) is a rare disease, which is still poorly characterized. In the present paper, we compared the hand perfusion of one female EM patient, under challenges, with a healthy control group. Using a laser Doppler flowmeter (LDF) with an integrated thermal probe, measurements were taken in both hands at rest (Phase I) and after two separate challenges-post-occlusive hyperemia (PORH) in one arm (A) and reduction of skin temperature (cooling) with ice in one hand (B) (Phase II). The final measurement periods corresponded to recovery (Phases III and IV). The control group involved ten healthy women (27.3 ± 7.9 years old). A second set of measurements was taken in the EM patient one month after beginning a new therapeutic approach with beta-blockers (6.25 mg carvedilol twice daily). Z-scores of the patient's LDF and temperature fluctuations compared to the control group were assessed using the Wavelet transform (WT) analysis. Here, fluctuations with |Z| > 1.96 were considered significantly different from healthy values, whereas positive or negative Z values indicated higher or lower deviations from the control mean values. Cooling elicited more measurable changes in LDF and temperature fluctuations, especially in higher frequency components (cardiac, respiratory, and myogenic), whereas PORH notably evoked changes in lower frequency components (myogenic, autonomic, and endothelial). No significant Z-score deviations were observed in the second measurement, which might signify a stabilization of the patient's distal perfusion following the new therapeutic approach. This analysis involving one EM patient, while clearly exploratory, has shown significant deviations in WT-derived physiological components' values in comparison with the healthy group, confirming the interest in using cold temperature as a challenger. The apparent agreement achieved with the clinical evaluation opens the possibility of expanding this approach to other patients and pathologies in vascular medicine.

Unveiling the role of osteosarcoma-derived secretome in premetastatic lung remodelling.

BACKGROUND: Lung metastasis is the most adverse clinical factor and remains the leading cause of osteosarcoma-related death. Deciphering the mechanisms driving metastatic spread is crucial for finding open therapeutic windows for successful organ-specific interventions that may halt or prevent lung metastasis. METHODS: We employed a mouse premetastatic lung-based multi-omics integrative approach combined with clinical features to uncover the specific changes that precede lung metastasis formation and identify novel molecular targets and biomarker of clinical utility that enable the design of novel therapeutic strategies. RESULTS: We found that osteosarcoma-bearing mice or those preconditioned with the osteosarcoma cell secretome harbour profound lung structural alterations with airway damage, inflammation, neutrophil infiltration, and extracellular matrix remodelling with increased deposition of fibronectin and collagens by resident stromal activated fibroblasts, favouring the adhesion of disseminated tumour cells. Systemic-induced microenvironmental changes, supported by transcriptomic and histological data, promoted and accelerated lung metastasis formation. Comparative proteome profiling of the cell secretome and mouse plasma identified a large number of proteins involved in extracellular-matrix organization, cell-matrix adhesion, neutrophil degranulation, and cytokine-mediated signalling, consistent with the observed lung microenvironmental changes. Moreover, we identified EFEMP1, an extracellular matrix glycoprotein exclusively secreted by metastatic cells, in the plasma of mice bearing a primary tumour and in biopsy specimens from osteosarcoma patients with poorer overall survival. Depletion of EFEMP1 from the secretome prevents the formation of lung metastasis. CONCLUSIONS: Integration of our data uncovers neutrophil infiltration and the functional contribution of stromal-activated fibroblasts in ECM remodelling for tumour cell attachment as early pro-metastatic events, which may hold therapeutic potential in preventing or slowing the metastatic spread. Moreover, we identified EFEMP1, a secreted glycoprotein, as a metastatic driver and a potential candidate prognostic biomarker for lung metastasis in osteosarcoma patients. Osteosarcoma-derived secreted factors systemically reprogrammed the lung microenvironment and fostered a growth-permissive niche for incoming disseminated cells to survive and outgrow into overt metastasis. Daily administration of osteosarcoma cell secretome mimics the systemic release of tumour-secreted factors of a growing tumour in mice during PMN formation; Transcriptomic and histological analysis of premetastatic lungs revealed inflammatory-induced stromal fibroblast activation, neutrophil infiltration, and ECM remodelling as early onset pro-metastatic events; Proteome profiling identified EFEMP1, an extracellular secreted glycoprotein, as a potential predictive biomarker for lung metastasis and poor prognosis in osteosarcoma patients. Osteosarcoma patients with EFEMP1 expressing biopsies have a poorer overall survival.

Make It Less Complex: Autoencoder for Speckle Noise Removal-Application to Breast and Lung Ultrasound.

Ultrasound (US) imaging is used in the diagnosis and monitoring of COVID-19 and breast cancer. The presence of Speckle Noise (SN) is a downside to its usage since it decreases lesion conspicuity. Filters can be used to remove SN, but they involve time-consuming computation and parameter tuning. Several researchers have been developing complex Deep Learning (DL) models (150,000-500,000 parameters) for the removal of simulated added SN, without focusing on the real-world application of removing naturally occurring SN from original US images. Here, a simpler (<30,000 parameters) Convolutional Neural Network Autoencoder (CNN-AE) to remove SN from US images of the breast and lung is proposed. In order to do so, simulated SN was added to such US images, considering four different noise levels (σ = 0.05, 0.1, 0.2, 0.5). The original US images (N = 1227, breast + lung) were given as targets, while the noised US images served as the input. The Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to compare the output of the CNN-AE and of the Median and Lee filters with the original US images. The CNN-AE outperformed the use of these classic filters for every noise level. To see how well the model removed naturally occurring SN from the original US images and to test its real-world applicability, a CNN model that differentiates malignant from benign breast lesions was developed. Several inputs were used to train the model (original, CNN-AE denoised, filter denoised, and noised US images). The use of the original US images resulted in the highest Matthews Correlation Coefficient (MCC) and accuracy values, while for sensitivity and negative predicted values, the CNN-AE-denoised US images (for higher σ values) achieved the best results. Our results demonstrate that the application of a simpler DL model for SN removal results in fewer misclassifications of malignant breast lesions in comparison to the use of original US images and the application of the Median filter. This shows that the use of a less-complex model and the focus on clinical practice applicability are relevant and should be considered in future studies.

Nanoparticle-Based Treatment in Glioblastoma.

Glioblastoma (GB) is a malignant glioma associated with a mean overall survival of 12 to 18 months, even with optimal treatment, due to its high relapse rate and treatment resistance. The standardized first-line treatment consists of surgery, which allows for diagnosis and cytoreduction, followed by stereotactic fractionated radiotherapy and chemotherapy. Treatment failure can result from the poor passage of drugs through the blood-brain barrier (BBB). The development of novel and more effective therapeutic approaches is paramount to increasing the life expectancy of GB patients. Nanoparticle-based treatments include epitopes that are designed to interact with specialized transport systems, ultimately allowing the crossing of the BBB, increasing therapeutic efficacy, and reducing systemic toxicity and drug degradation. Polymeric nanoparticles have shown promising results in terms of precisely directing drugs to the brain with minimal systemic side effects. Various methods of drug delivery that pass through the BBB, such as the stereotactic injection of nanoparticles, are being actively tested in vitro and in vivo in animal models. A significant variety of pre-clinical studies with polymeric nanoparticles for the treatment of GB are being conducted, with only a few nanoparticle-based drug delivery systems to date having entered clinical trials. Pre-clinical studies are key to testing the safety and efficacy of these novel anticancer therapies and will hopefully facilitate the testing of the clinical validity of this promising treatment method. Here we review the recent literature concerning the most frequently reported types of nanoparticles for the treatment of GB.

Phylogenetic relationships, distribution, and conservation of Roosmalens' dwarf porcupine, Coendouroosmalenorum Voss & da Silva, 2001 (Rodentia, Erethizontidae).

The New World porcupines of the genus Coendou comprise 16 species of arboreal nocturnal rodents. Some of these species are poorly known and have not been included in phylogenetic analyses. Based on recently collected specimens with associated tissue from the Brazilian Amazonia, we investigate the distribution and phylogenetic relationships of Roosmalens' dwarf porcupine, Coendouroosmalenorum, using an integrative approach using mitochondrial gene sequences and morphological data from new specimens and localities. Our results recovered C.roosmalenorum in the subgenus Caaporamys. However, analyses of our molecular and combined datasets produced different topologies. The new record shows the presence of C.roosmalenorum 480 km to the southeast of the Rio Madeira and 95 km away from Rio Juruena in Mato Grosso state, indicating a wider distribution in southern Amazonia than suspected. All known records of C.roosmalenorum are in the Madeira biogeographical province, to which it might be endemic.

Urinary Biomarkers and Point-of-Care Urinalysis Devices for Early Diagnosis and Management of Disease: A Review.

Biosensing and microfluidics technologies are transforming diagnostic medicine by accurately detecting biomolecules in biological samples. Urine is a promising biological fluid for diagnostics due to its noninvasive collection and wide range of diagnostic biomarkers. Point-of-care urinalysis, which integrates biosensing and microfluidics, has the potential to bring affordable and rapid diagnostics into the home to continuing monitoring, but challenges still remain. As such, this review aims to provide an overview of biomarkers that are or could be used to diagnose and monitor diseases, including cancer, cardiovascular diseases, kidney diseases, and neurodegenerative disorders, such as Alzheimer's disease. Additionally, the different materials and techniques for the fabrication of microfluidic structures along with the biosensing technologies often used to detect and quantify biological molecules and organisms are reviewed. Ultimately, this review discusses the current state of point-of-care urinalysis devices and highlights the potential of these technologies to improve patient outcomes. Traditional point-of-care urinalysis devices require the manual collection of urine, which may be unpleasant, cumbersome, or prone to errors. To overcome this issue, the toilet itself can be used as an alternative specimen collection and urinalysis device. This review then presents several smart toilet systems and incorporated sanitary devices for this purpose.

Low-Grade Mammary Gland Tumors in Dogs Have Greater VEGF-A and BMP2 Immunostaining and Higher CD31 Blood Vessel Density.

Tumor angiogenesis is an important process in tumor growth, and different molecules are involved in its regulation including VEGF-A, BMP2, and CD31, which can be considered possible prognostic markers. The aim of this study was to verify whether the VEGF-A and BMP2 immunostaining area, and microvascular density (MVD) might be associated with the degree of malignancy in malignant mammary neoplasms of dogs. For this purpose, samples of mammary malignancies from female dogs embedded in wax were used and separated into 4 main histomorphological types: tubulopapillary carcinomas, solid, complex, and carcinosarcoma, which were separated based on high and low degrees of malignancy. Immunohistochemical analysis was performed on tissue microarray blocks using anti-CD31 antibodies for evaluation of MVD and vascular lumen area, and with anti-VEGF-A and anti-BMP2 to determine the immunostaining area using the DAKO EnVision FLEX+ kit. MVD and vascular lumen area were higher in tubulopapillary carcinomas as were the areas stained by VEGF-A and BMP2. Immunostaining for CD31 was higher in low-grade carcinomas as well as in areas immunostained by VEGF-A and BMP2. There was a positive correlation between VEGF and BMP2 in high (r = 0.556, P < .0001) and low-grade (r = 0.287, P < .0001) carcinomas and between MVD and VEGF-A in low-grade carcinomas (r = 0.267, P = .0064). Thus, the markers evaluated showed greater immunostaining in canine mammary tumors with a lower degree of malignancy.

Normative model detects abnormal functional connectivity in psychiatric disorders.

Introduction: The diagnosis of psychiatric disorders is mostly based on the clinical evaluation of the patient's signs and symptoms. Deep learning binary-based classification models have been developed to improve the diagnosis but have not yet reached clinical practice, in part due to the heterogeneity of such disorders. Here, we propose a normative model based on autoencoders. Methods: We trained our autoencoder on resting-state functional magnetic resonance imaging (rs-fMRI) data from healthy controls. The model was then tested on schizophrenia (SCZ), bipolar disorder (BD), and attention-deficit hyperactivity disorder (ADHD) patients to estimate how each patient deviated from the norm and associate it with abnormal functional brain networks' (FBNs) connectivity. Rs-fMRI data processing was conducted within the FMRIB Software Library (FSL), which included independent component analysis and dual regression. Pearson's correlation coefficients between the extracted blood oxygen level-dependent (BOLD) time series of all FBNs were calculated, and a correlation matrix was generated for each subject. Results and discussion: We found that the functional connectivity related to the basal ganglia network seems to play an important role in the neuropathology of BD and SCZ, whereas in ADHD, its role is less evident. Moreover, the abnormal connectivity between the basal ganglia network and the language network is more specific to BD. The connectivity between the higher visual network and the right executive control and the connectivity between the anterior salience network and the precuneus networks are the most relevant in SCZ and ADHD, respectively. The results demonstrate that the proposed model could identify functional connectivity patterns that characterize different psychiatric disorders, in agreement with the literature. The abnormal connectivity patterns from the two independent SCZ groups of patients were similar, demonstrating that the presented normative model was also generalizable. However, the group-level differences did not withstand individual-level analysis implying that psychiatric disorders are highly heterogeneous. These findings suggest that a precision-based medical approach, focusing on each patient's specific functional network changes may be more beneficial than the traditional group-based diagnostic classification.

Highlighted Advances in Therapies for Difficult-To-Treat Brain Tumours Such as Glioblastoma.

Glioblastoma multiforme (GBM) remains a challenging disease, as it is the most common and deadly brain tumour in adults and has no curative solution and an overall short survival time. This incurability and short survival time means that, despite its rarity (average incidence of 3.2 per 100,000 persons), there has been an increased effort to try to treat this disease. Standard of care in newly diagnosed glioblastoma is maximal tumour resection followed by initial concomitant radiotherapy and temozolomide (TMZ) and then further chemotherapy with TMZ. Imaging techniques are key not only to diagnose the extent of the affected tissue but also for surgery planning and even for intraoperative use. Eligible patients may combine TMZ with tumour treating fields (TTF) therapy, which delivers low-intensity and intermediate-frequency electric fields to arrest tumour growth. Nonetheless, the blood-brain barrier (BBB) and systemic side effects are obstacles to successful chemotherapy in GBM; thus, more targeted, custom therapies such as immunotherapy and nanotechnological drug delivery systems have been undergoing research with varying degrees of success. This review proposes an overview of the pathophysiology, possible treatments, and the most (not all) representative examples of the latest advancements.

Removal of arsenic from semiarid area groundwater using a biosorbent from watermelon peel waste.

Groundwater is one of the most important reservoirs in semi-arid and arid zones of the world, particularly in Mexico. The aims of this work were to produce a biosorbent from watermelon peel waste and a biosorbent with citric acid treatment and to evaluate both biosorbents with different concentrations of arsenic in groundwater. The biosorbents were produced with watermelon peel residues, which were observed by SEM microscopy to evaluate their physical morphology. Its removal potential was tested at concentrations of 0, 1, 13, 22, and 65 µg/L of arsenic, and both adsorption capacity and removal percentage were analyzed by final measurement obtained by atomic absorption spectrometry. The pH was measured throughout the experimentation maintaining ranges between 5.5 and 7.5. The biosorbent without treatment presented clearer and more compact flakes. At the microscopic level, the biosorbent without treatment presented pores with a more circular shape, and the biosorbent with treatment was more polygonal, similar to a honeycomb. The highest removal percentage was 99.99%, for both treatments at 4 h. The biosorbent without treatment at 4 h with arsenic concentrations of 65 µg/L presented the highest adsorption capacity (2.42 µg/g). It is concluded that watermelon peel biosorbent is a material that has the potential to remove arsenic from groundwater. This type of biosorbent is effective to remove arsenic and could be used in the field, however, it still needs to be optimized to convert it into a material completely suitable for large-scale use.