University of Cauca

This study assessed the biodegradability of flexible film and its components. The tests were carried out under composting conditions. The kinetics of carbon dioxide production and the percentage of biodegradation were measured. Fourier Transform InfraRed spectroscopy (FTIR), Thermo Gravimetric Analysis (TGA), and Scanning Electron Microscopy (SEM) were used to study changes of the films in the biodegradation test. The total organic carbon (TOC) was measured. After the biodegradation test, plant growth tests were carried out, which included measurement of chlorophyll Index (CI). The results showed that the flexible film, ecovio F2223, and thermoplastic starch (TPS) achieved biodegradation of 92.13%, 93.20%, and 96.88%, respectively, in contrast to the polylactic acid‐PLA (80.28%). The FTIR showed changes in molecular structures, mainly in band crystalline zones around 2800–3000 cm⁻¹, deformation bands between 1400 and 1500 cm⁻¹ and in amorphous zones band of 1200–1000 cm⁻¹. TGA to flexible films, PLA, ecovio F2223, and TPS showed a thermal degradation around 350°C, 360°C, 370°C, and 320°C, due to polymeric structures degradation. SEM micrographs show morphology change on the films surfaces after the biodegradation test, evidencing the action of microorganisms. The plant growth tests showed the compost stability by Gemination percentage and CI no presented significative differences.

Occurring throughout the Americas, ceramics with negative decoration have been variously used as archaeological markers of chronology, provenance, ethnic affiliation, or cultural interaction. In the highlands of the adjacent regions of Nariño (Colombia) and Carchi (Ecuador), they are recovered and discussed frequently, but the lack of technical studies has prevented any conclusive inferences about their technology, craft organisation, or diachronic evolution. Here we present the first comparative analysis of the chaînes opératoires of three ceramic wares – Capulí, Piartal, and Tuza – based on a large sample from multiple sites. Combining geometric morphometrics, bulk chemistry, microscopy, and microanalysis, we provide high-resolution characterisation of each ware before comparing their chaînes opératoires. We demonstrate that Capulí and Piartal share decorative features and production pathways, which we interpret as indicating the direct knowledge transmission and interaction between their makers. Similarity in vessel morphology and clay sources between Piartal and Tuza ceramics suggests continuity between these two technological traditions, but new decorative techniques and designs in Tuza vessels are strongly indicative of exogenous influences. This study has implications for regional archaeology but also offers a model for the nuanced comparison of ceramic traditions in other areas (for an extended summary in Spanish, see Supplementary Material).

Microgravity, defined by minimal gravitational forces, represents a unique environment that profoundly influences biological systems, including human cells. This review examines the effects of microgravity on biological processes and their implications for human health. Microgravity significantly impacts the immune system by disrupting key mechanisms, such as T cell activation, cytokine production, and macrophage differentiation, leading to increased susceptibility to infections. In cancer biology, it promotes the formation of spheroids in cancer stem cells and thyroid cancer cells, which closely mimic in vivo tumor dynamics, providing novel insights for oncology research. Additionally, microgravity enhances tissue regeneration by modulating critical pathways, including Hippo and PI3K-Akt, thereby improving stem cell differentiation into hematopoietic and cardiomyocyte lineages. At the organ level, microgravity induces notable changes in hepatic metabolism, endothelial function, and bone mechanotransduction, contributing to lipid dysregulation, vascular remodeling, and accelerated bone loss. Notably, cardiomyocytes derived from human pluripotent stem cells and cultured under microgravity exhibit enhanced mitochondrial biogenesis, improved calcium handling, and advanced structural maturation, including increased sarcomere length and nuclear eccentricity. These advancements enable the development of functional cardiomyocytes, presenting promising therapeutic opportunities for treating cardiac diseases, such as myocardial infarctions. These findings underscore the dual implications of microgravity for space medicine and terrestrial health. They highlight its potential to drive advances in regenerative therapies, oncology, and immunological interventions. Continued research into the biological effects of microgravity is essential for protecting astronaut health during prolonged space missions and fostering biomedical innovations with transformative applications on Earth.

Depression is a common mental illness magnified by the COVID-19 pandemic. In this context, early depression detection is pivotal for public health systems. Various works have addressed depression detection in social network data. Nevertheless, they used data from before the pandemic and did not exploit Transformers’ architecture capabilities for realizing binary classification on extensive dimensional data. This paper aims to introduce a model based on encoder-only Transformer architecture to detect depression using a large Twitter dataset collected during the COVID-19 pandemic. In this regard, we present DEENT, an approach that includes a depression-oriented dataset built with BERT and K-means from a previous Twitter dataset labeled for sentiment analysis, and two models called DEENT-Generic and DEENT-Bert for classifying depressive and non-depressive tweets effectively. DEENT was evaluated extensively and compared to Random Forest, Support Vector Machine, XGBoost, Recurrent and Convolutional Neural Networks, and MentalBERT. Results revealed that DEENT-Bert outperforms baseline models regarding accuracy, balanced accuracy, precision, recall, and F1-Score for classifying non-depressive and depressive tweets. DEENT-Generic was better at detecting depressive tweets than baseline models. We argue that these results are due to the DEENT leveraging the encoder-only Transformer architecture and fine-tuning to detect depression in large Twitter data effectively. Therefore, we concluded that DEENT is a promising solution for detecting depressive and non-depressive tweets.

Patients with Alzheimer’s disease (AD) have two types of abnormal protein buildups: amyloid plaques and neurofibrillary tangles, in addition to the early synaptic dysfunction associated with the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). Impairment of the glutamatergic system is also crucial for neuronal survival, as it can cause synaptic dysfunction that overstimulates glutamate receptors, especially N-methyl-d-aspartate receptors (NMDARs). Another protein affecting neuronal health is glycogen synthase kinase-3 (GSK3), a widely preserved serine/threonine protein kinase linked to neuronal disorders, including AD. In recent years, alkaloids from the Amaryllidaceae have received great attention for their known anticholinergic activity, as well as their antioxidant, antigenotoxic, and neuroprotective properties. In this context, the identification of compounds capable of interacting with different targets involved in AD provides a possible new therapeutic strategy. In this study, we conducted a combination of in vitro and in silico approaches to identify the potential of C. subedentata in regulating key proteins involved in AD. Viability and neuroprotection assays were performed to evaluate the neuroprotection exerted by C. subedentata extract against neurotoxicity induced by Aβ (1–42) peptide and Okadaic acid in SH-SY5Y cells. Computational methods such as docking and molecular dynamic and viability therapeutic analysis were conducted to explore the interaction of alkaloids from C. subedentata with target proteins (AChE, BuChE, NMDA, and GSK-3) involved in AD. Our findings show that C. subedentata extract exerts neuroprotective effects against neurotoxic stimuli induced by Aβ (1–42) peptide and Okadaic acid. In addition, in silico approaches provide insight into how C. subedentata extract alkaloids interact with key proteins involved in AD. These findings provide insights into the potential therapeutic effects and action mechanisms of these alkaloids. We hope these rapid findings can contribute as a bridge to the identification of new molecules with the potential to counteract the effects of AD.

Background A key target of the 2030 Sustainable Development Goals is to eliminate preventable deaths in newborns and children under 5. This study aimed to estimate the effect of time of birth on early neonatal mortality (ENM) and low Apgar scores at 5 min (LA5) in newborns. Methods A retrospective cohort study was conducted using vital statistics data on live births, maternal morbidity, congenital defects and perinatal mortality in Cauca-Colombia (2017–2021) excluding out-of-hospital, multiple and major defect cases. A directed acyclic graph was constructed to define the confounder adjustment set. Multivariable logistic, linear and propensity score models evaluated the effect of birth timing on neonatal outcomes, estimating crude and adjusted incidence rate ratios (IRRa). Results We assessed 65 182 live births, finding similar baseline characteristics for daytime and night-time births. ENM was 0.2% (95% CI 0.19% to 0.26%) at 7 days of follow-up, absolute mortality difference 0.1% (95% CI –0.01% to 0.12%). Night-time births increased the incidence of ENM in the primary analysis IRRa 1.27 (95% CI 0.90 to 1.82), in the secondary IRRa 1.45 (95% CI 0.94 to 2.20), and in the primary and secondary sensitivity analysis, respectively, IRRa 1.48 (95% CI 1.06 to 2.07) and 1.70 (95% CI 1.16 to 2.59). LA5 was present in 0.7% (95% CI 0.60% to 0.72%) of birth, with absolute LA5 difference 0.1% (95% CI –0.02% to 0.22%). Night-time births increased the incidence of LA5 in the primary analysis IRRa 1.31 (95% CI 1.00 to 1.49), in the secondary IRRa 1.44 (95% CI 1.13 to 1.83), and in the primary and secondary sensitivity analysis, respectively, IRRa 1.31 (95% CI 1.08 to 1.59) and IRRa 1.54 (95% CI 1.23 to 1.92). Conclusions Birth at night-time is associated with worse neonatal outcomes, ENM and low Apgar scores in Colombia’s diverse population, highlighting the need for optimised prenatal care, revised work schedules and improved referral systems in maternal health.

We find that viscous and viscoelastic fluids are distinguishable by gauging Non‐Fickian diffusion of dissolved electroactive molecules. Typically, such fluids are differentiated by measuring the mean‐squared‐displacement <Δr²> of embedded tracer particles (~1 μm) diffusing over time (t). From the relationship <Δr²>=6Dtα (D=particle diffusivity), log plots of <Δr²>vs.tα reveal regimes encoded in the slope α. For Fickian diffusion α=1, whereas α<1 and α>1, indicate Non‐Fickian sub‐ and super‐diffusion, respectively. Here, we electrolyzed redox reporters as molecular tracers in selected fluids. The current (I) relationship I ∝ ${\propto }$ v1/2 (v=scan‐rate) was recast as I²vs.1/tα to introduce α as Non‐Fickian quantifier in log plots. When viscosity increased at high concentration of small‐molecules, D for the redox reporter declined but α remained constant at ~1 (Fickian). In contrast, both D and α(<1) decreased in viscoelastic hydrogels confirming a molecular sub‐diffusive regime. These results agree with particle microrheology on the same fluid types using optical methods that are inapplicable to molecules. By quantifying Non‐Fickian diffusion of electroactive molecular tracers, our method can uncover diffusion‐structure relationships to identify regulators in neurodegenerative liquid‐solid transitions of protein aggregates. Unlike tracer particles, the diffusivity of tracer molecules is controlled by the applied potential and electrode size.

In this work, zinc oxide nanoparticles (ZnO-NPs) were synthesized using a chemical route. The ZnO obtained was characterized using infrared and Raman spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results indicated that the synthesized ZnO had a unique crystal structure corresponding to the wurtzite type. The primary particles of the synthesized oxide had a size < 100 nm, a crystallite size of ~ 33.20 nm and spheroidal morphology. These primary particles formed agglomerates with an average size of ~ 460 nm. The bandgap values of the synthesized ZnO were between ~ 2.7 and 2.8 eV, with an Urbach energy of ~ 340 meV. Considering the potential use of synthesized ZnO-NPs and commercial ZnO (ZnO-MPs) in agriculture, seeds of C. annuum were exposed to treatments at concentrations of 0, 10, 20, 50, 100 and 200 mg L⁻¹ of ZnO-NPs or ZnO-MPs to determine their biological effect. A relevant result was the decrease in the dry weight of the plumule, in the proportion indicated in parentheses, of the seedlings obtained from seeds exposed to ZnO-NPs, in concentrations of 10 mg L⁻¹ (15%), 20 mg L⁻¹ (17%) and 200 mg L⁻¹ (13%), or treated with ZnO-MPs, in concentrations of 10 mg L⁻¹ (19%) and 100 mg L⁻¹ (13%). These treatments could cause toxicity in the seedling since the reduction in the recorded dry weight was equal to or greater than 10%, a percentage considered as a benchmark for the critical level of toxicity.

This study evaluated the effect of replacing fish meal (FM) with concentrated trout viscera protein hydrolysate (TVPH) on the immune response in juvenile red tilapia (Oreocheromis spp). Five isoenergetic and isoproteic experimental diets were prepared by substituting FM with TVPH at different substitution ratios: 0% (control, D1) 25% (D2), 50% (D3), 75% (D4), and 100% (D5). A total of 180 red tilapia were distributed in 15 tanks. Fish from three tanks were fed daily at 2% of the biomass for 25 days with one of the five diets mentioned above. At the end of the trial, the fish were counted, weighed, measured, and skin mucus and serum samples were obtained to study different parameters related to humoral immunity. The results indicate a 100% survival rate in all fish groups and did not show significant differences in terms of growth and feed efficiency. On the other hand, the fish fed diets D2 and D3 had significantly higher serum protein values. Also, fish fed the D2 or D5 diets had higher lysozyme activity and fish fed the D2 diet also had significantly higher total immunoglobulin levels than fish fed the control diet. In mucus, fish fed the D2 or D4 diets showed significantly higher mucus protein levels than control fish. However, anti-protease and bactericidal activity decreased in fish fed the D5 or D4 diets, respectively. These results demonstrate that the D2 and D3 diets positively modulate the immune response of juvenile red tilapia compared to that of fish fed the control diet.

During the post-harvest of coffee and plantain, organic residues with high potential for utilization are generated. This work aimed to measure the effect of extrusion on the nutritional, physicochemical, and functional properties of mixtures of coffee pulp (CP), rejected plantain (RP), and plantain rachis (PR) flours. The residues were dehydrated, milled, and mixed according to the simplex reticular experimental design. Subsequently, the mixtures were extruded. The properties before and after extrusion were determined. It was found that the effect of extrusion reduced the crude fiber and lipid content composition, but protein and ash content were not changed. A positive relation was found between coffee pulp flour and rachis plantain flour in response to total phenolic content (TPC) and antioxidant activity (AA). Some blends increased the TPC and AA but others reduced it. At the same time, water activity and water and oil absorption capacity showed a significant extrusion effect, while the pH did not. It was determined that the optimum mixture extruded was 0.364:0.333:0.303 of CP, RP, and PR, respectively. Extrusion reduced all pasting properties of the optimized blend. The flours studied presented a relevant nutritional and functional contribution, which favors their viability for use in the food industry.

In this letter, we prove that strongly regular graphs and Deza digraphs do not exist with parameters (pm,k,2m,2m)$(p^m,k,2^m,2^m)$ where m=3,4m=3,4. As a consequence, we provide many parameters for which there is no a difference set.

We find that viscous and viscoelastic fluids are distinguishable by gauging Non‐Fickian diffusion of dissolved electroactive molecules. Typically, such fluids are differentiated by measuring the mean‐squared‐displacement <Δr2> of embedded tracer particles (~1 μm) diffusing over time (t). From the relationship <Δr2>=6Dtα (D=particle diffusivity), log plots of <Δr2>vs.tα reveal regimes encoded in the slope α. For Fickian diffusion α=1, whereas α<1 and α>1, indicate Non‐Fickian sub‐ and super‐diffusion, respectively. Here, we electrolyzed redox reporters as molecular tracers in selected fluids. The current (I) relationship I[[EQUATION]]v1/2 (v = scan‐rate) was recast as I2vs.1/tα to introduce α as Non‐Fickian quantifier in log plots. When viscosity increased at high concentration of small‐molecules, D for the redox reporter declined but α remained constant at ~1 (Fickian). In contrast, both D and α(<1) decreased in viscoelastic hydrogels confirming a molecular sub‐diffusive regime. These results agree with particle microrheology on the same fluid types using optical methods that are inapplicable to molecules. By quantifying Non‐Fickian diffusion of electroactive molecular tracers, our method can uncover diffusion‐structure relationships to identify regulators in neurodegenerative liquid‐solid transitions of protein aggregates. Unlike tracer particles, the diffusivity of tracer molecules is controlled by the applied potential and electrode size.

In this study, a system was developed to predict anemia using blood count data and supervised learning algorithms. Anemia, a common condition characterized by low levels of red blood cells or hemoglobin, affects oxygenation and often causes symptoms, such as fatigue and shortness of breath. The diagnosis of anemia often requires laboratory tests, which can be challenging in low-resource areas where anemia is common. We built a supervised learning approach and trained three models (Linear Discriminant Analysis, Decision Trees, and Random Forest) using an anemia dataset from a previous study by Sabatini in 2022. The Random Forest model achieved an accuracy of 99.82%, highlighting its capability to subclassify anemia types (microcytic, normocytic, and macrocytic) with high precision, which is a novel advancement compared to prior studies limited to binary classification (presence/absence of anemia) of the same dataset.

Technology is essential for the improvement and efficiency of activities in the agricultural environment. Nevertheless, farmers and IT’s worlds are distant. Usually, IT services fail to provide the correct solution and farmers are reluctant to incorporate new IT advances. IT teams need to acquire agricultural knowledge and language in order to communicate, to reduce the distance, and cooperate. Nevertheless, during this process and particularly, in agriculture, there are many uncertainties. If they are not clearified, it will not be possible to provide the right IT solution. These uncertainties are translated as a lack of precision in the requirements specifications. Sometimes, it is as easy as elicit more information from the stakeholders to improve the specification. In some other situations, the stakeholders have different points of view and they need to reach a concensus. These uncertainties are hard to identify. IT teams and farmers must speak the same technical and specific language and the IT team needs a complete and exhaustive specification about how software applications must react. Agriculture is a biological environment with many rules and decisions that are not easy to make explicit. Therefore, it is important to involve a group of farmers as with complementary and different point of view. Thus, this article proposes an approach to deal with uncertainties in order to provide the unambiguous and complete specification. The approach relies on capturing knowledge through scenarios. It consists of three main steps to obtain the scenarios: (i) a collaborative knowledge acquisition, (ii) scenarios description and analysis, and (iii) group decision support.

Intestinal parasitism is an infection that affects people worldwide, with populations in developing countries being at a higher risk of acquiring it. This infection is contracted for various reasons, mainly related to poor sanitary conditions and inadequate food practices, leading to multiple health issues such as malnutrition, intestinal obstructions, epilepsy, and others. Identifying parasitic species is essential for establishing appropriate antiparasitic therapy, which in turn helps reduce the risk of associated morbidities. For this reason, a dataset named “ParasitoBank” was created, containing 779 images of the visual field of fresh stool samples analysed under a microscope using the serial coprological technique. These images were acquired using a Motorola G84 mobile phone, and a data-labeling process resulted in a total of 1,620 intestinal parasites, with a particular focus on intestinal protozoa. The images have an approximate aspect ratio of 1:1 with a resolution of 2100 × 2100. Label information and some metadata for the images have been included in a JSON file following the “Common Objects in Context” (COCO) format. Finally, the entire dataset and label content have been arranged in a compressed file. The presented information facilitates the use of the data for various studies, spanning education and artificial intelligence development.

The physicochemical and structural characteristics of coffee husks obtained by humid medium were determined, from coffee grown in the municipality of Pitalito, Colombia. For this, the physicochemical characterization was carried out. Among the most significant results was the considerable fiber content of the husks, at around 70%. Of this, 17.86% corresponds to lignin. In light of this and reviewing the other parameters analyzed, it can be established that coffee husks show important and promising structural characteristics for use in the manufacture of biodegradable products, in addition to highlighting the content of microelements such as potassium, calcium, phosphorus, and magnesium, which can further serve to encourage their use.

Introduction Before implementing a new health care strategy, it is important to assess effectiveness but also to perform an economic evaluation. The goal of the present study was to perform a comparative economic evaluation of a new strategy aimed at using proposed implementation of the Plateletworks guidance (measurement of platelet function) with usual practice (delayed time to surgery) in patients on chronic antiplatelet treatment and scheduled for surgery with neuraxial anaesthesia due to proximal femur fracture. Methods This is an economic evaluation carried out alongside a randomised controlled clinical trial at four centres in Spain. Patients were randomised to undergo either early platelet function-guided surgery (experimental group) or delayed surgery (control group). As AFFEcT trial results demonstrated significative difference between groups in the primary efficacy endpoint, the median time to surgery, a cost-effectiveness analysis was performed. Direct costs associated with hospitalisation until one-month post-discharge were considered and measured from a hospital perspective. All costs were reported in euros. Analyses were performed on a per protocol basis. Effectiveness outcome measures were the incremental cost and incremental cost per reduction in days to surgery. A deterministic sensitivity analysis was implemented to quantify uncertainty. Results A total of 156 patients were randomized to the two groups ( n = 78 per group). A total of 143 patients were included in the per protocol population (75 and 68 patients in the experimental and control groups, respectively). The median time to surgery was 2.30 days (IQR: 1.53–3.73) in the experimental group and 4.87 days (4.36–5.60) in the control group (a reduction of 2.40 days). Total costs during the 1-month study perioperative period were higher in the delayed surgery group (€18,495.19) than for the early surgery group (€16,497.59). The incremental cost was negative (€1,997.60), a statistically significant difference ( P < 0.05). As measured by the reduction in time (days) to surgery, the incremental cost-effectiveness ratio (ICER) for early surgery was negative (777.28€/day). Sensitivity analysis demonstrated consistent cost saving. Conclusion For patients on chronic antiplatelet treatment scheduled to undergo surgery for proximal femur fracture, an individualised strategy guided by a platelet function testing is a cost-saving and cost-effective strategy.

Background Conventional fish feed based on fish meal, meat, and soy cake presents procurement difficulties and high costs, affecting the profitability and sustainability of the aquaculture industry. Objective To evaluate the effect of hydrolyzed red worm (HRW- Eisenia foétida ) in red tilapia ( Oreochromis sp. ) diet on production parameters. Methods The study was conducted at the aquaculture farm of the Politécnico Colombiano Jaime Isaza Cadavid (PCJIC) at 780 m.a.s.l.,with an average temperature of 28 °C. Ninety red tilapia fingerlings, averaging 7,5±0,5 g, were distributed in nine aquariums containing 75 liters of water. Fish underwentweight and size measurements at the beginning and end of the trial. They were fed experimental diets to apparent satiation three times daily. Water quality parameters and productive rates of growth and nutrient utilization were measured. The experimental design included three treatments with three replicates each: T1 (control diet, 0% hydrolysate inclusion), T2 (10% hydrolysate inclusion), and T3 (20% hydrolysate inclusion). ANOVA (p<0,05) was applied to growth and nutrient utilization variables, with mean comparisons using α<0,05 in SPSS version 25. Results Significant differences (p<0,04) were found between the control diet T1 (0% inclusion) and T2 (10% inclusion) in favor of weight gain (31,87 g). There were no statistical differences in size increase (p<0,217). As HRWinclusion increased, feed consumption decreased, likely due to higher hydrolyzed protein availability. Feed conversion rates showed significant differences (p<0,001) between T2 and T3 compared to T1, indicating better assimilation of the hydrolyzed protein. T2 and T3 also showed better protein and energy efficiency (p<0,001), demonstrating the hydrolyzed protein’s nutritional quality and assimilation. Diet cost decreased with higher hydrolyzed inclusion (p<0,034). Conclusion Inclusion 10% and 20% hydrolyzed red worms significantly improved production parameters and reduced costs, making it a viable alternative for feeding red tilapia for small and medium-scale producers.

Introduction In recent years, the increased demand for food has prompted farmers to increase production to support economic expansion. However, the excessive use of mineral fertilizers poses a significant threat to the sustainability of food systems. In Colombia, coffee cultivation plays a fundamental role in the economy, thus creating a recognized demand to elevate its production while minimizing its environmental impact sustainably. Methodology The study follows the CRISP-DM methodology (Cross-Industry Standard Process for Data Mining) developing of a fertilizer recommender system (FRS) for coffee crops. This process includes business understanding, where the key factors influencing coffee production were identified; data understanding and preparation, where agroclimatic data and expert knowledge were collected and processed; modeling, which involved building a case-based reasoning (CBR) system to recommend fertilizer doses and frequencies, and evaluation, where expert feedback was gathered to assess the system's performance. The CBR system integrates soil, crop, and climate variables to provide tailored recommendations for nitrogen, phosphorus, and potassium applications. Results The results revealed that the FRS was deemed acceptable for application in the region, with expert evaluations rating the recommendations based on their experience and knowledge. Additionally, valuable feedback was provided to facilitate future enhancements to the system. Discussion Based on expert feedback and system performance, the proposed FRS meets the minimum requirements for deployment in real crops, serving as a valuable tool for small-scale farmers. Future work will expand the case base and refine recommender algorithms to improve accuracy and usability.

Background: Post-traumatic stress disorder (PTSD) is a psychophysiological condition caused by traumatic experiences. Its diagnosis typically relies on subjective tools like clinical interviews and self-reports. Objectives: This scoping review analyzes computational methods using EEG signal processing for PTSD diagnosis, differentiation, and therapy. It provides a comprehensive overview of the entire EEG analysis pipeline, from acquisition to statistical and machine learning techniques for PTSD diagnosis. Methods: Using the PRISMA-ScR protocol, studies published between 2013 and 2024 were reviewed from databases including Scopus, Web of Science, and PubMed. A total of 73 studies were analyzed: 52 on diagnosis, 8 on differentiation, and 15 on therapy. Results: EEG Bands and Event-Related Potentials (ERP) were the dominant techniques. The Alpha band demonstrated strong performance in diagnosis and therapy. LPP ERP was most effective for diagnosis, and P300 for differentiation. Supervised SVM models achieved the highest accuracy in diagnosis (ACC = 0.997), differentiation (ACC = 0.841), and psychotherapy (ACC = 0.78). Random Forest multimodal models integrating EEG with other modalities (e.g. ECG, GSR, Speech) achieved ACC = 0.993. Unsupervised approach is employed to cluster patients to identify PTSD subtypes or to differentiate PTSD from other mental disorders. Veterans and combatants were the primary study population, and only three studies reported open datasets. Conclusions: EEG-based methods hold promise as objective tools for PTSD diagnosis and therapy. The review identified limitations in the use of ERP, sleep characterization and full-band EEG. Broader datasets representing diverse populations are essential to mitigate bias and facilitate robust inter-model comparisons. Future research should focus on deep learning, adaptive signal decomposition, and multimodal approaches.