Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr

Well Test Analysis of Inclined Wells in the Low-Permeability Composite Gas Reservoir Considering the Non-Darcy Flow

The application of traditional well test interpretation methods cannot comprehensively consider characteristics of stress sensitivity and non-Darcy flow for low-permeability composite gas reservoirs, which makes it difficult to obtain real reservoir parameters. Based on the micro-mechanism analysis of stress sensitivity and non-Darcy flow in low-permeability gas reservoirs, the flow motion equation was improved. Thus, a mathematical model was established which belongs to the inclined well in the composite gas reservoir with a conventional internal zone and low-permeability external zone. Applying the finite element method to solve the flow model through Matlab programming, the equivalent pressure point was selected to research the pressure distribution of the inclined well. On this basis, the bottom hole pressure dynamic curve was drawn, the flow process was divided into seven stages, and the parameter sensitivity analysis was carried out. Finally, the advanced nature of the new model applied to the interpretation of the well test model is compared by conventional methods. The non-Darcy flow can cause the gradual upward warping of the bottom hole pressure dynamic curve in the later stage, and non-linear enhancement leads to an increase in the upturn through the simulation test. When the inclination angle is greater than 60°, early vertical radial flow and mid-term linear flow gradually appear. A decrease leads to a shorter duration of the pseudo radial flow in the internal zone and the radius of the internal zone. The conduction coefficients ratio of internal and external zones affects the pseudo pressure derivative curve slope in transition phase of pseudo radial flow in the internal and external zones. A comprehensive consideration of the low-permeability composite gas reservoir flow characteristics can improve the fitting degree of the pressure curves. Not only that, but it can also solve the strong diversification of reservoir parameters. Results have a guiding significance for low-permeability composite gas reservoir development and pressure dynamic evaluation in inclined wells

Interaction between Negatively Charged Fish Gelatin and Cyclodextrin in Aqueous Solution: Characteristics and Formation Mechanism

The effect that ratios of fish gelatin (FG) to α/β/γ cyclodextrins (α, β, γCDs) had on the phase behavior of a concentrated biopolymer mixture were comparatively investigated. This showed that the formed biopolymer mixture had the highest gel strength at ratios of FG–CD = 90:10. FG could interact with CDs to form stable soluble complexes with lower values of turbidity, particle size and ζ-potential. All of the FG–CD mixture solutions exhibited pseudo-plastic behaviors, and FG–αCD samples had the highest viscosity values than others. The addition of CDs could unfold FG molecules and make conformation transitions of FG from a random coil to β-turn, leading to the environmental change of hydrophobic residues and presenting higher fluorescence intensity, especially for βCDs. FTIR results revealed that the formation of intermolecular hydrogen bonds between FG and CD could change the secondary structure of FG. These findings might help further apply FG–CD complexes in designing new food matrixes

Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs

Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in the developing fetus. Manual segmentation of fetal brain tissue is cumbersome and time-consuming, so using an automatic segmentation method can greatly simplify the process. In addition, the fetal brain undergoes a variety of changes throughout pregnancy, such as increased brain volume, neuronal migration, and synaptogenesis. In this case, the contrast between tissues, especially between gray matter and white matter, constantly changes throughout pregnancy, increasing the complexity and difficulty of our segmentation. To reduce the burden of manual refinement of segmentation, we proposed a new deep learning-based segmentation method. Our approach utilized a novel attentional structural block, the contextual transformer block (CoT-Block), which was applied in the backbone network model of the encoder–decoder to guide the learning of dynamic attentional matrices and enhance image feature extraction. Additionally, in the last layer of the decoder, we introduced a hybrid dilated convolution module, which can expand the receptive field and retain detailed spatial information, effectively extracting the global contextual information in fetal brain MRI. We quantitatively evaluated our method according to several performance measures: dice, precision, sensitivity, and specificity. In 80 fetal brain MRI scans with gestational ages ranging from 20 to 35 weeks, we obtained an average Dice similarity coefficient (DSC) of 83.79%, an average Volume Similarity (VS) of 84.84%, and an average Hausdorff95 Distance (HD95) of 35.66 mm. We also used several advanced deep learning segmentation models for comparison under equivalent conditions, and the results showed that our method was superior to other methods and exhibited an excellent segmentation performance

Table1_The spatial impact of digital economy on carbon emissions reduction: evidence from 215 cities in China.docx

Introduction: Within the global framework of carbon emissions constraints, the digital economy has become a new strategy for cities to achieve sustainable development. Scholarly literature exploring the spatial spillover and spatial mechanisms of the digital economy on carbon emissions is notably scarce.Methods: To estimate the spatial impact of digital economy on carbon emissions, this paper conducted spatial analysis with the spatial Dubin model and panel data of 215 cities in China from 2011 to 2019.Results: The results show that there is a growing regional agglomeration of the digital economy, whereas the spatial evolution of carbon emissions displays low liquidity and high stability. Second, the digital economy directly reduces urban carbon emissions, and this conclusion is supported through a series of robustness tests. However, there exist negative spatial spillover effects of digital economy on carbon emissions reduction in neighboring cities. Third, mechanism analysis reveals that the digital economy mainly affects urban carbon emissions through two paths: industrial structure upgrading and green technology innovation. Moreover, the influence of digital economy exhibits heterogeneity, with a more pronounced effect observed in the central cities and in large and medium-sized cities, as well as in cities with a high agglomeration of the new energy industry.Discussion: Our paper not only presents new documentary evidence for understanding the relationship between digitalization and decarbonization, but also provides specific references for policy making to accelerate low-carbon urban development.</p

Prediction of Mg Alloy Corrosion Based on Machine Learning Models

Magnesium alloy is a potential biodegradable metallic material characterized by bone-like elastic modulus, which has great application prospects in medical, automotive, and aerospace industries owing to its bone-like elastic modulus, biocompatibility, and lightweight properties. However, the rapid corrosion rates of magnesium alloys seriously limit their applications. This study collected magnesium alloys’ corrosion data and developed a model to predict the corrosion potential, based on the chemical composition of magnesium alloys. We compared four machine learning algorithms: random forest (RF), multiple linear regression (MLR), support vector machine regression (SVR), and extreme gradient boosting (XGBoost). The RF algorithm offered the most accurate predictions than the other three machine learning algorithms. The input effects on corrosion potential have been investigated. Moreover, we used feature creation (transforming chemical component characteristics into atomic and physical characteristics) so that the input characteristics were not limited to specific chemical compositions. From this result, the model’s application range was widened, and machine learning was used to verify the accuracy and feasibility of predicting corrosion of magnesium alloys

MBNL2 promotes aging-related cardiac fibrosis via inhibited SUMOylation of Krüppel-like factor4

Summary: Aging-related cardiac fibrosis represents the principal pathological progression in cardiovascular aging. The Muscleblind-like splicing regulator 2 (MBNL2) has been unequivocally established as being associated with cardiovascular diseases. Nevertheless, its role in aging-related cardiac fibrosis remains unexplored. This investigation revealed an elevation of MBNL2 levels in the aged heart and senescent cardiac fibroblasts. Notably, the inhibition of MBNL2 demonstrated a capacity to mitigate H2O2-induced myofibroblast transformation and aging-related cardiac fibrosis. Further mechanistic exploration unveiled that aging heightened the expression of SENP1 and impeded the SUMO1 binding with KLF4, and SUMOylation of KLF4 effectively increased by the inhibition of MBNL2. Additionally, the inhibition of TGF-β1/SMAD3 signaling attenuated the impact of over-expression of MBNL2 in inducing senescence and cardiac fibrosis. MBNL2, by orchestrating SUMOylation of KLF4, upregulating the TGF-β1/SMAD3 signaling pathway, emerges as a significant promoter of aging-related cardiac fibrosis. This discovery identifies a novel regulatory target for managing aging-related cardiac fibrosis

Reactivating PTEN to impair glioma stem cells by inhibiting cytosolic iron-sulfur assembly pathway

&lt;p&gt;Glioblastoma (GBM), the most lethal primary brain tumor, harbors glioma stem cells (GSCs) that not only initiate and maintain malignant phenotypes but also enhance therapeutic resistance. Although frequently mutated in GBMs, the function and regulation of PTEN in PTEN-intact GSCs are unknown. Here we found that PTEN directly interacts with MMS19 and competitively disrupts MMS19-based cytosolic iron-sulfur (Fe-S) cluster assembly (CIA) machinery in the differentiated glioma cells (DGCs). Interrogation of GSCs, when compared with their matched DGCs, revealed that PTEN is specifically succinated at cysteine (C) 211 in GSCs. Isotope tracing coupled with mass spectrometry analysis confirmed that fumarate, generated by adenylosuccinate lyase (ADSL) in &lt;em&gt;de novo&lt;/em&gt; purine synthesis pathway which is highly activated in GSCs, promotes PTEN C211 succination. This modification abrogates the interaction between PTEN and MMS19, thereby reactivating CIA machinery pathway in GSCs. Functionally, inhibiting PTEN C211 succination through re-expressing PTEN C211S mutant, depleting ADSL, or consuming fumarate by N-acetylcysteine (NAC), an FDA-approved prescription drug, impairs GSC maintenance. Importantly, re-expressing PTEN C211S or treating with NAC sensitizes GSC-derived brain tumors to temozolomide and irradiation, the standard-of-care treatments for GBM patients, by retarding CIA machinery-mediated DNA damage repair. These findings reveal an immediately practicable strategy to target GSCs for treating GBMs by combined therapy with repurposing NAC.&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 82072765&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 81972610&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 82272651&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 82172667&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 82002914&lt;/p&gt;&lt;p&gt;Funding provided by: Government of Jiangsu Province&lt;br&gt;Crossref Funder Registry ID: https://ror.org/004svx814&lt;br&gt;Award Number: ZDXK202225&lt;/p&gt;&lt;p&gt;Funding provided by: China Postdoctoral Science Foundation&lt;br&gt;Crossref Funder Registry ID: https://ror.org/0426zh255&lt;br&gt;Award Number: 2023M731767&lt;/p&gt;&lt;p&gt;Funding provided by: Nanjing Medical University&lt;br&gt;Crossref Funder Registry ID: https://ror.org/059gcgy73&lt;br&gt;Award Number: GSBSHKY202203&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Mice&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;To identify the potential tumor formation ability of GSCs and DGCs, luciferase-expressing cells (1 × 10&lt;sup&gt;4&lt;/sup&gt;) were injected intracranially into 4-week-old female athymic old nude mice (BALB/cNj-Foxn1nu/Gpt, Strain NO. D000521, GemPharmatech) as previously described (&lt;em&gt;25&lt;/em&gt;). Each group contained five mice. Mice were fed autoclaved food and water and maintained in a specific pathogen-free facility. Tumor volumes were monitored by detecting the flux activity using a bioluminescence imaging system at different time points.&lt;/p&gt; &lt;p&gt;To teste whether inhibiting PTEN C211sc sensitizes GSCs to TMZ treatment, PTEN-depleted-MGG8 or MES28 GSCs expressing with or without WT Flag-PTEN or Flag-PTEN C211S were transfected with firefly luciferase. 1 × 10&lt;sup&gt;4 &lt;/sup&gt;cells were injected intracranially into 4-week-old female athymic old nude mice. Each group contained five mice. 7 days after the injection, mice were treated with PBS or TMZ (20 mg/kg) by intraperitoneal injection. To teste whether inhibiting PTEN C211sc sensitizes GSCs to radiation treatment, PTEN-depleted-MGG8 or MES28 GSCs expressing with or without WT Flag-PTEN or Flag-PTEN C211S were transfected with firefly luciferase. 1 × 10&lt;sup&gt;4 &lt;/sup&gt;cells were injected intracranially into 4-week-old female athymic old nude mice. Each group contained five mice. On day 9 and 11, mice receive 5 Gy radiation treatment. Tumor volumes were monitored by detecting the flux activity using a bioluminescence imaging system at different time points.&lt;/p&gt; &lt;p&gt;To explore the function of NAC sensitizing chemotherapy of brain tumors, 1 × 10&lt;sup&gt;4&lt;/sup&gt; luciferase-expressing MGG8 and T3264 GSCs were injected intracranially into 4-week-old female athymic old nude mice. Each group contained five mice. 7 days after the injection, mice were treated with PBS, TMZ (20 mg/kg), NAC (200 mg/kg), or TMZ plus NAC by intraperitoneal injection. To explore the function of NAC sensitizing radiation therapy of brain tumors, 1 × 10&lt;sup&gt;4&lt;/sup&gt; luciferase-expressing MGG8 and T3264 GSCs were injected intracranially into 4-week-old female athymic old nude mice. Each group contained five mice. 7 days after the injection, mice were treated with NAC (200 mg/kg) by intraperitoneal injection. On day 9 and 11, mice receive 5 Gy radiation treatment. Tumor volumes were monitored by detecting the flux activity using a bioluminescence imaging system at different time points.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Cell Culture&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;GSCs (MGG8, T3264, CW839, T2907, GSC23, MES28, MES20, T3028 and CW738) were derived from human specimens as previously described (PMID: 30948495). Details of these patients are restricted by the institutional requirements. GSCs were maintained in &lt;a&gt;N&lt;/a&gt;eurobasal medium (Life Technologies) supplemented with B27, L-glutamine, sodium pyruvate, 10 ng/ml basic fibroblast growth factor and 10 ng/ml epidermal growth factor (R&amp;D Systems). For inducing DGCs, Fetal Bovine Serum (FBS) was added into culture medium for 7 days, and culture medium was changed every other day. The GSC phenotype was validated by stem cell marker expression (SOX2, Olig2 and GFAP) and tumor propagation &lt;em&gt;in vivo&lt;/em&gt;.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Plasmids and lentiviral transduction&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Polymerase chain reaction (PCR)-amplified full-length or truncated human FH, Flag-PTEN, and HA-MMS19 were cloned into the pLVX vector. Human CIAO1 and CIAO2B were cloned into pColdI (His) vector. PTEN C211S was generated using the QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA). shRNA-resistant (r) PTEN was constructed by introducing nonsense mutations in shRNA-targeting sites as previously described (&lt;em&gt;10&lt;/em&gt;). shRNA targeting PTEN (5'-GCCAGCTAAAGGTGAAGATATAT-3') was inserted into the pGIPZ vector as previously described (&lt;em&gt;10&lt;/em&gt;). Lentiviral clones expressing shRNAs against human MMS19 (TRCN0000096384), human ADSL (TRCN0000078271), human PRPS1 (TRCN0000010123), human PPAT (TRCN0000031614) or a control shRNA were purchased from Sigma-Aldrich (St. Louis, MO, USA). 293FT cells were used to generate lentiviral particles through co-transfection of the packaging vectors pCMV-dR8.2 and pCI-VSVG using a standard calcium phosphate transfection method in Neurobasal complete medium as previously described (&lt;em&gt;25&lt;/em&gt;).&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Immunoprecipitation and Immunoblotting Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Protein samples were extracted from transfected GSCs using IP cell lysis buffer (50 mM Tris-HCl, pH 7.5, 0.01% SDS, 1% Triton X-100, 150 mM NaCl, 1 mM dithiothreitol, 0.5 mM EDTA, 100 μM PMSF, 100 μM leupeptin, 1 μM aprotinin, 100 μM sodium orthovanadate, 100 μM sodium pyrophosphate, and 1 mM sodium fluoride). Immunoblot and immunoprecipitation analyses were performed using indicated antibodies as previously described (&lt;em&gt;58&lt;/em&gt;).&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Purification of Recombinant Proteins&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Expression of His-CIAO1 and CIAO2B were induced in bacteria, and protein purification was performed as previously described (&lt;em&gt;58&lt;/em&gt;). Briefly, 6xHis-tagged recombinant proteins were cultured in 250 ml of lysogeny broth (LB) medium until the OD reached 0.6. 0.5 mM. Isopropyl β-D-1-thiogalactopyranoside (IPTG) was used to induce protein expression overnight at 16 ℃. Then, bacteria were collected and lysed. The cell lysates were loaded onto a Ni-NTA column, washed with five column volumes of 20 mM imidazole, and eluted with 250 mM imidazole. Purified proteins were desalted using 10-kDa cut-through spin columns by washing with PBS.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Neurosphere Formation Assay&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&lt;em&gt;In vitro&lt;/em&gt; limiting dilution was performed to measure neurosphere formation as previously described. Briefly, decreasing numbers of GSCs (100, 50, 25, 10, 2) per well were plated into 96-well plates. The presentation and numbers of neurospheres in each well were recorded. Extreme limiting dilution analysis was performed using software available at http://bioinf.wehi.edu.au/software/elda as previously described (&lt;em&gt;5&lt;/em&gt;).&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Quantitative RT-PCR&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Total cellular RNA was isolated using Trizol reagent (Sigma Aldrich). The qScript cDNA Synthesis Kit (Quanta BioSciences) was used for reverse transcription into cDNA. Applied Biosystems 7900HT cycler using SYBR-Green PCR Master Mix (Thermo Fisher Scientific) was employed to perform quantitative real-time PCR. The primers used in this study were described in Table S4.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Cell Proliferation Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;A total of&lt;strong&gt; &lt;/strong&gt;1000 GSCs suspended in 200 μL Neurobasal medium were plated in a 96-well plate. CellTiter-Glo (Promega, Madison, WI, USA) was used to measure cell proliferation according to the manufacturer's instructions. All data were normalized to those of day 1 and presented as mean ± SD from three independent experiments.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;&lt;sup&gt;55&lt;/sup&gt;&lt;/strong&gt;&lt;strong&gt;Fe Incorporation Assay&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&lt;sup&gt;55&lt;/sup&gt;Fe incorporation assays were performed as previously described (&lt;em&gt;21&lt;/em&gt;). Briefly, 16 mM &lt;sup&gt;55&lt;/sup&gt;FeCl3 (Perkin Elmer) was incubated in 100mM HCl, 63 μM nitrilotriacetic acid (NTA), and 20 mM HEPES pH to 6.0 with Tris followed by titration to pH 7.0 with 100 mM NaOH to obtain &lt;sup&gt;55&lt;/sup&gt;Fe-NTA. 1 × 10&lt;sup&gt;5&lt;/sup&gt; cells were seeded into 6-well plates followed by 2 mCi/mL &lt;sup&gt;55&lt;/sup&gt;Fe-NTA treatment for 18 hours. Then, cells were washed, collected, and lysed using RIPA buffer (150 mM NaCl, 5 mM EDTA pH 8.0, 50 mM Tris-HCl pH 8.0, 1% NP-40 (v/v), 0.5% sodium deoxycholate (w/v), 0.1% SDS (w/v), 1 mM DTT, and 1X protease inhibitor cocktail (Roche)). MMS19 targeting proteins were Immunoprecipitated and &lt;sup&gt;55&lt;/sup&gt;Fe incorporation was measured by scintillation counting. Data were normalized to cellular protein concentrations.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Fumarate Quantification&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Intracellular fumarate levels were quantified using Fumarate Assay Kit (MAK060, Sigma-Aldrich) according to manufacturer's instructions. For intracellular fumarate measurement, 1 × 10&lt;sup&gt;6&lt;/sup&gt; cells were lysed using fumarate assay buffer from the kit, followed by centrifuging at 13,000 g for 10 min to remove insoluble material. For intracranial fumarate measurement, mice were perfused with PBS. The tumor samples in mouse brains were collected and chopped into pieces. 4 mg tissues were rapidly homogenized in 10 mL of Fumarate Assay Buffer, followed by centrifuging at 13,000 g for 10 min to remove insoluble material. Set up the Master Reaction Mix using fumarate assay buffer, fumarate developer, and fumarate enzyme mix from the kit. Add 100 μL Master Reaction Mix to each well of plates from the kit, followed by incubation for 30 min at room temperature. Measure the absorbance at 450 nm and calculate fumarate levels. Data were normalized to cellular protein concentrations.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Mass Spectrometry Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;PTEN succination site was determined as previously described (&lt;em&gt;10&lt;/em&gt;). Briefly, Flag-PTEN protein was immunoprecipitated from two GSC cultures (MGG8 and T3264) and digested by dithiothreitol (5 mM) for 30 min at 56 ℃ followed by alkylation with iodoacetamide (11 mM) for 15 min at room temperature in a dark environment. Then, protein was diluted to concentration less than 2 M using TEAB (100 mM). Finally, chymotrypsin (chymotrypsin : protein = 1 : 50) was used to digest protein twice. After digestion, the protein peptides were analyzed by MALDI-TOF/TOF MS (MALDI-7090, Shimadzu Kratos). The total MS/MS data was compared against SwissProt Database by the following parameters: chymotrypsin digestion allowing up to 1 missed cleavage, fixed modifications of cysteine (carbamidomethylation), variable modifications of methionine (oxidation) and cysteine (succination), precursor peptide tolerance of 0.05 Da, and MS/MS tolerance of 0.2 Da. Analysis results with e values less than 0.01 was considered as positive identifications.&lt;/p&gt; &lt;p&gt;To confirm the results that purine synthesis fuels PTEN C211sc through ADSL, MGG8 GSCs expressing with control shRNA or ADSL shRNA were washed with aspartate-free medium and incubated in fresh medium containing &lt;sup&gt;13&lt;/sup&gt;C-aspartate (1 mM) for 24 h. &lt;sup&gt;13&lt;/sup&gt;C-labelled C211sc of PTEN was analyzed by MS as described above.&lt;/p&gt; &lt;p&gt;To determine the abundance of intracellular IMP, AMP, GMP, and GSH, approximately 1 × 10&lt;sup&gt;5&lt;/sup&gt; GSCs were seeded in 10 cm dishes in triplicate. Cells were lysed, extracted in 90/9/1 (v/v/v) acetonitrile/water/formic acid and subjected to high-resolution mass spectrometry. Pure samples of IMP, GMP, AMP and GSH were purchased from Sigma-Aldrich. Samples were centrifuged and supernatants were dried using Termovap Sample Concentrator. Samples were then resolved in ammonium acetate (10 mM) containing 0.2% ammonium hydroxide. Samples were injected into a Luna NH2 column (P/N 00B-4378-B0; 5 μM, 50 × 2.0 mm; Phenomenex, Torrance, CA) heated to 35°C with mobile phase A (0.77 g NH4OAc, 1.25 mL NH4OH, 25 mL ACN, and 300 µL acetic acid [HAc] dissolved in 500 mL water) and mobile phase B (acetonitrile). Using a flowrate of 0.3ml/min, the elution program was: 0.1 min, 85% B; 3 min, 30% B; 12 min, 2% B; 15 min, 2% B; and 16–28 min, 85% B. Data were acquired using a Thermo Orbitrap Fusion Tribrid Mass Spectrometer via Selected Ion Mode (SIM) electrospray positive mode.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;EC&lt;sub&gt;50&lt;/sub&gt; Measurement&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;GSCs were exposed to TMZ with increasing concentrations from 2.9 to 1500 μM. Cell viability was measured at 24 h after treatment. The EC&lt;sub&gt;50&lt;/sub&gt; of TMZ for GSCs was calculated using GraphPad software.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Combination Effect Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;The synergistic effect of TMZ and NAC combination was evaluated by a calculation of CI according to the Chou-Talalay method. Data were analyzed using CompuSyn software (CompuSyn Inc.): CI = 0.85 to 0.9, slight synergism; CI = 0.7 to 0.85, moderate synergism; CI = 0.3 to 0.7, synergism; CI = 0.1 to 0.3, strong synergism; CI &lt; 0.1, very strong synergism.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Immunohistochemical (IHC) Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Sections of paraffin-embedded xenografted tumors were stained with Ki-67, γ-H2AX, PTEN, and PTEN C211sc, respectively. The percentage of Ki-67 and γ-H2AX positive cells was quantified in five randomly selected fields using Image Pro Plus software (Media Cybernetics). The staining of PTEN and PTEN C211sc were quantified according to the percentage of positive cells and staining intensity as described previously. The staining intensity was scored on a scale of 0-3: 0, negative; 1, weak; 2, moderate; and 3, strong. The proportion scores were assigned to the sections: 0 if 0% of tumor cells exhibited positive staining, 1 for 0 to 1% positive cells, 2 for 2% to 10% positive cells, 3 for 11% to 30% positive cells, 4 for 31% to 70% positive cells, and 5 for 71% to 100% positive cells. The intensity and proportion scores were then added to obtain a total score ranging from 0 to 8 as described before.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;TUNEL Analysis&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;GSCs-derived tumors were cut into 4 mm slices. The rate of apoptotic cells in tumors was analyzed using the TUNEL BrightGreen Apoptosis Detection Kit (Vazyme) according to the manufacturer's instructions.&lt;/p&gt