Accurate Database Research Articles

Phase Equilibrium Study of Rare Earth Oxide–Fluoride Salt System: A Review

The applications of rare earth metals and alloys are becoming increasingly widespread and there is a strong market demand. Currently, most of the production enterprises adopt the fluoride–oxide system for electrolytic preparation of rare earth metals and alloys. The solubility of rare earth oxides in molten salt directly affects the selection of operational parameters in the electrolysis process. When the added amount of RE2O3 is less than its solubility, it leads to a decreased electrolytic efficiency. Conversely, an excessive amount of oxide is prone to settle at the bottom of the electrolytic cell, impeding smooth production. The RE2O3 solubility in the fluoride salt can be represented by the phase equilibrium of the RE2O3-REF3-LiF system. The isothermal lines in the primary phase field of rare earth oxide represent the solubility of the oxide in the fluoride salt at the corresponding temperature. This paper outlines the research methods and experimental results on the phase equilibria of the RE2O3-REF3-LiF system. The characteristics and existing problems in the current phase equilibrium study are analyzed. The solubility data of RE2O3 are expressed in the forms of ternary and pseudo-binary phase diagrams of the RE2O3-REF3-LiF system, providing theoretical guidance for the establishment of an accurate and reliable rare earth electrolysis system database and the optimization of electrolytic processes.

Efficient Vertical Structure Correlation and Power Line Inference.

High-resolution three-dimensional data from sensors such as LiDAR are sufficient to find power line towers and poles but do not reliably map relatively thin power lines. In addition, repeated detections of the same object can lead to confusion while data gaps ignore known obstacles. The slow or failed detection of low-salience vertical obstacles and associated wires is one of today's leading causes of fatal helicopter accidents. This article presents a method to efficiently correlate vertical structure observations with existing databases and infer the presence of power lines. The method uses a spatial hash key which compares an observed tower location to potential existing tower locations using nested hash tables. When an observed tower is in the vicinity of an existing entry, the method correlates or distinguishes objects based on height and position. When applied to Delaware's Digital Obstacle File, the average horizontal uncertainty decreased from 206 to 56 ft. The power line presence is inferred by automatically comparing the proportional spacing, height, and angle of tower sets based on the more accurate database. Over 87% of electrical transmission towers were correctly identified with no false negatives.

Preserving a Legacy: Ensuring the Access and Conservation of the Harold (Harry) G. Fowler (19502018) Ant Collection and Data.

Biological collections are important repositories of biodiversity, as they include various types of data potentially useful to different areas of science and can contribute to the establishment of biodiversity conservation policies. For a long time, scientific collections were considered only as physical databases; in this context Harold G. Fowler (19502018) built an ant collection at the Universidade Estadual Paulista, campus Rio Claro (So Paulo state, Brazil), over the course of a 34-year career, comprising around 20,000 ant specimens. Most specimens came from the Brazilian Atlantic Forest, but many others came from distinct locations in Brazil and abroad. After his death, the collection was left without the necessary curatorial care for a period of time, which required a project to be conceived for its recovery and conservation, with the goal of incorporating it to the Zoology Museum of the University of So Paulo (MZSP). In addition to applying modern technical curation protocols, other activities such as checking, material identification and digitization of the information contained on the sample labels were carried out, forming an accurate database. This process enabled the identification of new distribution records and the discovery of possible undescribed species and unpublished natural history data. After validating this information, we counted 524 valid species and 201 morphospecies belonging to 105 genera and 10 subfamilies. In addition, we integrated technical curation activities with scientific outreach to draw the general publics attention to the importance of biological collections, thus fostering interest in science, biodiversity and nature conservation. Our work highlights the importance of preserving the areas sampled by Fowlers research group. The preservation of vouchers using curatorial practices reinforces the role of scientific collections as important tools for the study, understanding and preservation of biodiversity.

A CALPHAD thermodynamic model for multicomponent alloys under pressure and its application in pressurized solidified Al–Si–Mg alloys

High pressure technology has been utilized as an important means to regulate phase structure and improve the properties/performance of alloys. The CALPHAD approach based on accurate databases has great advantages in efficient alloy design. However, the application of CALPHAD in high pressure field is hindered by the lack of reliable thermodynamic model/database for multicomponent alloys under pressure. In this paper, a phenomenologically thermodynamic model for multicomponent alloys under pressure is first developed by separating the contribution into two parts, one is at atmosphere pressure and the other is caused by an increase in pressure, and then successfully applied to establish the pressure-dependent thermodynamic database of ternary Al–Si–Mg system. The calculated phase equilibria/thermodynamic properties of pressure dependence in related alloys are in good agreement with the limited experimental data in the literature, validating the reliability of the obtained thermodynamic database. After that, a CALPHAD design framework for pressurized solidified alloys is proposed by integrating the present pressure-dependent thermodynamic model/database, CALPHAD-type calculations/simulations, and previously developed high-throughput calculation platform Malac-Distmas. Such a framework is finally applied to predict the pressurized solidification and high pressure heat treatment behaviors in different Al–Si–Mg alloys. The predicted microstructure, phase transitions and phase equilibria after pressurized solidification and high pressure heat treatment are consistent with the experimental data. Furthermore, the insights into effect of pressure on the thermodynamic essence of alloys are gained, which may definitely facilitate the advancement of alloy design under high pressure technology.

Review of methods for estimating the prevalence of rare diseases

One of the main challenges in rare diseases is the unavailability of reliable estimates of prevalence and incidence. The lack of epidemiological data makes planning for therapeutic and management options challenging. Methods for estimating the prevalence and incidence of rare and genetic diseases primarily rely on the availability of accurate national patient registries or databases of birth defects. This gap is wider in Low- and Middle-Income countries (LMICs) such as India, where currently, the estimates of prevalence and incidence are either unknown or data from developed countries have to be used as a proxy. Here, we analyzed the current methods used to estimate the prevalence and incidence of rare genetic diseases to provide recommendations in the form of a decision tree to select the most feasible method, particularly in resource-constrained environments such as India. We selected ten rare diseases of shared importance to the Indo US Organization for Rare Diseases (IndoUSrare) and its Patients Alliance members for analysis. Our analysis suggests that retrospective study designs are the most commonly used method to estimate the prevalence and incidence of rare diseases. We propose a generalized decision tree or flowchart to aid epidemiology researchers during the selection of methods for estimating the prevalence and incidence of a rare or genetic disease.

Dismantling Quantity Estimation for Nuclear Power Plant: Scan-to-BIM versus Conventional Method

This paper presents a case study of using Scan-to-BIM technology for evaluating the quantity and cost of a nuclear power plant during the decommissioning process. The study proposes a process for applying Scan-to-BIM in the dismantling stage and develops a BIM-based VPL (Visual Programming Language) to acquire accurate as-is databases that are crucial for nuclear power plants handling radioactive materials. The proposed process and system were applied to K-1 NPP (Nuclear Power Plant), the first nuclear power plant in Korea, and the results were compared to those obtained using the conventional method. The study found that errors in quantity evaluation using the conventional method ranged from around 10% to over 10 times, and were attributed to various causes such as outdated as-is drawings and limitations in expressing information in drawings. By using the Scan-to-BIM process and system, errors in quantity evaluation were significantly reduced, and the conventional method was found to have underestimated the dismantling cost by 20%. The findings of this study provide important insights for the efficient and accurate decommissioning of nuclear power plants, and demonstrate the effectiveness of the proposed method and system for evaluating the quantity and cost of a nuclear power plant during the decommissioning process.

Strategies to Improve the Quantum Computation Accuracy for Electrochemical Windows of Ionic Liquids.

Rational design of ionic liquids (ILs) with wide electrochemical windows (ECWs) for high-voltage cathodes is essential to elevating the energy density of current rechargeable batteries. It is significant to determine appropriate strategies for accurately predicting the ECWs of ILs. In this study, we compare the calculated ECWs based on three quantum methods, including the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) method, the ionization potential-electron affinity (IP-EA) method, and the thermodynamic method, under four unique combinations of simulation environments, and assess the discrepancies between the calculated and the experimental results of ECWs. For the three quantum methods, although HOMO-LUMO and IP-EA methods show limited prediction accuracy compared to the experimental values, they can qualitatively rank the anodic limits of anions and the cathodic limits of cations. For the thermodynamic method, we demonstrate that the highest accuracy can be achieved by considering the most rational redox reaction process. By varying the calculation environments, the calculated ECWs tend to be underestimated by considering separate cations and anions of ILs under gas phase, whereas they always exhibit overestimated results when calculating based on the cation-anion pairs. When the computation considers isolated ions with the solvent model plus proper thermodynamic corrections, we observe improved consistency with the experimental results. Though all methods have limitations to achieving perfect predictions of ECWs, we believe rational selection of calculation methods based on application-oriented scenarios can balance the efficiency and accuracy of the results for the development of a high-throughput and accurate database of ECWs for ILs.

Probabilistic Linkage Creates a Novel Database to Study Bronchiolitis Care in the PICU.

Lack of a comprehensive database containing diagnosis, patient and clinical characteristics, diagnostics, treatments, and outcomes limits needed comparative effectiveness research (CER) to improve care in the PICU. Combined, the Pediatric Hospital Information System (PHIS) and Virtual Pediatric Systems (VPS) databases contain the needed data for CER, but limits on the use of patient identifiers have thus far prevented linkage of these databases with traditional linkage methods. Focusing on the subgroup of patients with bronchiolitis, we aim to show that probabilistic linkage methods accurately link data from PHIS and VPS without the need for patient identifiers to create the database needed for CER. We used probabilistic linkage to link PHIS and VPS records for patients admitted to a tertiary children's hospital between July 1, 2017 to June 30, 2019. We calculated the percentage of matched records, rate of false-positive matches, and compared demographics between matched and unmatched subjects with bronchiolitis. We linked 839 of 920 (91%) records with 4 (0.5%) false-positive matches. We found no differences in age (P = .76), presence of comorbidities (P = .16), admission illness severity (P = .44), intubation rate (P = .41), or PICU stay length (P = .36) between linked and unlinked subjects. Probabilistic linkage creates an accurate and representative combined VPS-PHIS database of patients with bronchiolitis. Our methods are scalable to join data from the 38 hospitals that jointly contribute to PHIS and VPS, creating a national database of diagnostics, treatment, outcome, and patient and clinical data to enable CER for bronchiolitis and other conditions cared for in the PICU.

DEVELOPMENT OF WEB GIS APPLICATIONS FOR MONITORING AGRICULTURAL ACTIVITIES IN SUNGAI KAKAP DISTRICT, KUBU RAYA REGENCY

<p>Good agricultural development planning requires an accurate and real-time database. This is very important to see the development and level of welfare of farmers as the spearhead of food security. Sungai Kakap Sub-district, Kubu Raya Regency is one of the sub-districts with the number of Gapoktan (23), Poktan (284), the number of members (6305) with Field Agricultural Extension Workers (PPL) since 2019 totalling 9 civil servants and 14 people helping themselves. The number of PPLs is not proportional to the number of farmer group members, making supervision of agricultural activities difficult. The presentation of information in the form of Web GIS is expected to be a solution so that assistance, guidance, and counselling carried out by the government through the agriculture office can be right on target. The purpose of this research is to build a Web GIS-based Agricultural Information System in Sungai Kakap District so that it can be used as a model for agricultural monitoring activities in other areas. The engineering method in this research uses Remote Sensing and Waterfall methods. Remote Sensing is a method of building spatial data using aerial photo interpretation techniques, while Waterfall is used to build a web GIS as a place to display spatial data. The result of this research is Software Engineering in the form of a Web GIS-based Agricultural Information System Application. This Web GIS application can then be used as a tool to monitor the agricultural activities of each farmer group member in each farmer group.</p>

A database of computed Raman spectra of inorganic compounds with accurate hybrid functionals

Raman spectroscopy is widely applied in identifying local structures in materials, but the interpretation of Raman spectra is non-trivial. An accurate computational database of reference spectra calculated with a consistent level of theory can significantly aid in interpreting measured Raman spectra. Here, we present a database of Raman spectra of inorganic compounds calculated with accurate hybrid functionals in density functional theory. Raman spectra were obtained by calculating dynamical matrices and polarizability tensors for structures from the Inorganic Crystal Structure Database. The calculated Raman spectra and other phonon properties (e.g., infrared spectra) are stored in a MongoDB database publicly shared through a web application. We assess the accuracy of our Raman calculations by statistically comparing ~80 calculated spectra with an existing experimental Raman database. To date, the database contains 161 compounds and is continuously growing as we add more materials computed with our automated workflow.

The Promise and Pitfalls of AI-Generated Anatomical Images: Evaluating Midjourney for Aesthetic Surgery Applications.

The rapid advancement of generative artificial intelligence (AI) systems, such as Midjourney, has paved the way for their use in medical training, producing computer-generated images. However, despite clear disclosures stating that these images are not intended for medical consultations, their accuracy and realism are yet to be thoroughly examined. A series of requests were addressed to the Midjourney AI tool, a renowned generative artificial intelligence application, with a focus on depicting appropriate systemic anatomy and representing aesthetic surgery operations. Subsequently, a blinded panel of four experts, with years of experience in anatomy and aesthetic surgery, assessed the images based on three parameters: accuracy, anatomical correctness, and visual impact. Each parameter was scored on a scale of 1-5. All of images produced by Midjourney exhibited significant inaccuracies and lacked correct anatomical representation. While they displayed high visual impact, their unsuitability for medical training and scientific publications became evident. The implications of these findings are multifaceted. Primarily, the images' inaccuracies render them ineffective for training, leading to potential misconceptions. Additionally, their lack of anatomical correctness limits their applicability in scientific articles. Although the study focuses on a single AI tool, it underscores the need for collaboration between AI developers and medical professionals. The potential integration of accurate medical databases could refine the precision of such AI tools in the future. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Nutritional interventional studies in patients with multiple sclerosis: a scoping review of the current clinical evidence.

A good nutritional status appears to slow down disease progression and ameliorate symptoms' intensity in patients with multiple sclerosis (MS). Up to date, there are several interventional studies, which have explored the potential beneficial effects of specific dietary patterns as well as specific bioactive nutrients against disease progression and symptomatology of MS patients. This is a thorough, scoping review, which aims to critically summarize and scrutinize the currently available clinical evidence of the potential beneficial effects of nutritional interventional studies against MS progression and symptomatology. This review was conducted to systematically map the research done in this area, as well as to identify gaps in knowledge. For this purpose, we thoroughly explored the most accurate scientific web databases, e.g., PubMed, Scopus, Web of Science, and Google Scholar to achieve the most relevant clinical human studies applying effective and characteristic keywords. There are currently several dietary patterns and specific bioactive nutrients that show promising results by slowing down disease progression and by improving MS symptoms. However, there are also certain conflicting results, while most of the existing studies enrolled a small number of MS patients. Nutritional interventions may exert substantial protective effects against MS progression and symptomatology. However, large, long-term, randomized, double-blind, controlled clinical trials with a prospective design are strongly recommended to delineate whether such nutritional intervention may attenuate disease progression, and improve symptomatology in MS patients.

Anti-obesity properties of phytochemicals: Highlighting their molecular mechanisms against obesity.

Obesity is a complex, chronic and inflammatory disease that affects more than one-third of the world's population, leading to a higher incidence of diabetes, dyslipidemia, metabolic syndrome, cardiovascular diseases, and some types of cancer. Several phytochemicals are used as flavoring and aromatic compounds, also exerting many benefits for public health. This study aims to summarize and scrutinize the beneficial effects of the most important phytochemicals against obesity. Systematic research of the current international literature was carried out in the most accurate scientific databases, e.g., Pubmed, Scopus, Web of Science and Google Scholar, using a set of critical and representative keywords, such as phytochemicals, obesity, metabolism, metabolic syndrome, etc. Several studies unraveled the potential positive effects of phytochemicals such as berberine, car-vacrol, curcumin, quercetin, resveratrol, thymol, etc., against obesity and meta-bolic disorders. Mechanisms of action include inhibition of adipocyte differentia-tion, browning of the white adipose tissue, inhibition of enzymes such as lipase and amylase, suppression of inflammation, improvement of the gut microbiota, and downregulation of obesity-inducing genes. In conclusion, multiple bioactive compounds-phytochemicals exert many beneficial effects against obesity. Future molecular and clinical studies must be performed to unravel the multiple molecu-lar mechanisms and anti-obesity activities of these naturally occurring bioactive compounds.

Convolutional Neural Networks Facilitate River Barrier Detection and Evidence Severe Habitat Fragmentation in the Mekong River Biodiversity Hotspot

AbstractConstruction of river infrastructure, such as dams and weirs, is a global issue for ecosystem protection due to the fragmentation of river habitat and hydrological alteration it causes. Accurate river barrier databases, increasingly used to determine river fragmentation for ecologically sensitive management, are challenging to generate. This is especially so in large, poorly mapped basins where only large dams tend to be recorded. The Mekong is one of the world's most biodiverse river basins but, like many large rivers, impacts on habitat fragmentation from river infrastructure are poorly documented. To demonstrate a solution to this, and enable more sensitive basin management, we generated a whole‐basin barrier database for the Mekong, by training Convolutional Neural Network (CNN)–based object detection models, the best of which was used to identify 10,561 previously unrecorded barriers. Combining manual revision and merged with the existing barrier database, our new barrier database for the Mekong Basin contains 13,054 barriers. Existing databases for the Lower Mekong documented under ∼3% of the barriers recorded by CNN combined with manual checking. The Nam Chi/Nam Mun region, eastern Thailand, is the most fragmented area within the basin, with a median [95% CI] barrier density of 15.53 [0.00–49.30] per 100 km, and Catchment Area‐based Fragmentation Index value, calculated in an upstream direction, of 1,178.67 [0.00–6,418.46], due to the construction of dams and sluice gates. The CNN‐based object detection framework is effective and potentially can transform our ability to identify river barriers across many large river basins and facilitate ecologically‐sensitive management.

Sulfoproteomics Workflow with Precursor Ion Accurate Mass Shift Analysis Reveals Novel Tyrosine Sulfoproteins in the Golgi.

Tyrosine sulfation in the Golgi of secreted and membrane proteins is an important post-translational modification (PTM). However, its labile nature has limited analysis by mass spectrometry (MS), a major reason why no sulfoproteome studies have been previously reported. Here, we show that a phosphoproteomics experimental workflow, which includes serial enrichment followed by high resolution, high mass accuracy MS, and tandem MS (MS/MS) analysis, enables sulfopeptide coenrichment and identification via accurate precursor ion mass shift open MSFragger database search. This approach, supported by manual validation, allows the confident identification of sulfotyrosine-containing peptides in the presence of high levels of phosphorylated peptides, thus enabling these two sterically and ionically similar isobaric PTMs to be distinguished and annotated in a single proteomic analysis. We applied this approach to isolated interphase and mitotic rat liver Golgi membranes and identified 67 tyrosine sulfopeptides, corresponding to 26 different proteins. This work discovered 23 new sulfoproteins with functions related to, for example, Ca2+-binding, glycan biosynthesis, and exocytosis. In addition, we report the first preliminary evidence for crosstalk between sulfation and phosphorylation in the Golgi, with implications for functional control.

High-efficient screening of pesticide residues in vegetables using gas chromatography/quadrupole time-of-flight (GC/Q-TOF)

Gas chromatography (GC) and liquid chromatography (LC) coupled with a triple quadrupole mass spectrometer using multiple reaction monitoring (MRM) mode is widely used for pesticide residue analysis. However, MRM mode cannot fulfill the requirements of high-throughput or non-target analysis. High-resolution mass spectrometry such as time-of-flight (TOF) with high mass accuracy enables targeted and non-targeted analysis. This study proposes a qualitative screening method using GC/quadrupole time-of-flight (GC/Q-TOF) to monitor vegetable pesticide residues based on the retention time and accurate mass database of the MassHunter Personal Compound Database and Library (PCDL). GC/Q-TOF screening identified 89 of 92 pesticides in 90 vegetable samples, resulting in a true positive rate of 96.7%. These results were in excellent agreement with those obtained from conventional LC-MS/MS and GC-MS/MS methods (Cohen’s Kappa = 0.82). Thiamethoxam exhibited the highest detection frequency at 13.75% (mostly below the MRL), with imported radishes showing the highest occurrence. Moreover, unexpected pesticides and metabolites, including cinmethylin, benzyl benzoate, 2,6-dichlorobenzamide, diethyltoluamide, and phthalimide, were detected. This proposed method enables qualitative screening of over 1000 pesticides without using expensive analytical standards. Further manual investigation can be conducted to mitigate false-positive results. Overall, this evaluation demonstrates that the combination of GC/Q-TOF with the commercial PCDL database is robust and suitable for pesticide screening in vegetables.

Integrating Bio-metric Authentication in E-challan Machine

In India, as of my last update in January 2023, it was not compulsory to link the Aadhaar card and driving license. However, the Aadhaar card, a unique identification document issued by the Indian government, and the driving license, a legal document that permits individuals to drive vehicles, can be linked for verification purposes. The proposed objective behind linking these documents was to streamline and authenticate personal information, reduce identity fraud, ensure a more accurate database, and make processes more efficient. It's recommended to verify the current status of linking Aadhaar and driving license with concerned authorities or the latest government regulations, as the specific requirements and status may have changed since my last update.

Efficient acquisition of interdiffusion coefficients matrices and atomic mobilities of fcc Co–Mn–Cr alloys by combining diffusion couple experiments and HitDIC software

Reliable diffusivities and atomic mobilities of fcc Co–Mn–Cr alloys are the important keystones for establishing the accurate diffusion database for CoCrFeMnNi high-entropy alloys and other relevant alloys, but they are still missing in the literature. In this paper, diffusion couple experiments together with High-throughput Determination of Interdiffusion Coefficients (HitDIC) software were employed to efficiently obtain diffusion descriptions of fcc Co–Mn–Cr alloys. Six diffusion couples were prepared and examined to provide the prerequisite composition profiles. Feature selection and regularization techniques in HitDIC software were adopted to extract the corresponding interdiffusion coefficients and atomic mobilities. A reliable set of diffusion descriptions of the fcc Co–Mn–Cr alloys were therefore obtained and verified. Investigations of the underlying composition- and temperature-dependent diffusion behaviors were enabled and demonstrated.

Exercise as a Promising Agent against Cancer: Evaluating Its Anti-Cancer Molecular Mechanisms

Background: Cancer cases are continuously increasing, while the prevalence rates of physical inactivity are also continuously increasing. Physical inactivity is a causative factor in non-communicable diseases, including cancer. However, the potential beneficial effects of exercise on cancer treatment have not received much attention so far. The aim of this study was to highlight the relationship between cancer and exercise on a molecular basis. Methods: Comprehensive and in-depth research was conducted in the most accurate scientific databases by using relevant and effective keywords. Results: The mechanisms by which exercise may reduce cancer risk and/or progression may include the metabolic profile of hormones, systemic inflammation reduction, insulin sensitivity increase, antioxidant capacity augmentation, the boost to the immune system, and the direct effect on the tumor. There is currently substantial evidence that the effect of exercise may predict a stronger association with cancer and could supplementarily be embedded in cancer clinical practice to improve disease progression and prognosis. Conclusion: The field of this study requires interconnecting the overall knowledge of exercise physiology with cancer biology and cancer clinical oncology to provide the basis for personalized targeting strategies that can be merged with training as a component of a holistic co-treatment approach to optimize cancer healthcare.

May Nutritional Status Positively Affect Disease Progression and Prognosis in Patients with Esophageal and Pharyngeal Cancers? A Scoping Review of the Current Clinical Studies.

Malnutrition in esophageal and pharyngeal cancer patients constitutes a common and serious concern, which significantly reduces patients' prognoses. Cancers of the esophagus and the pharynx can considerably impair feeding in patients, resulting in severe undernutrition. This is a scoping review that intends to critically analyze the most well-designed clinical studies investigating the potential beneficial impact of diverse nutritional assessment tools on the prognosis of patients with esophageal and pharyngeal cancers. The most accurate and remarkable scientific databases were comprehensively explored utilizing relative keywords to detect clinical studies that investigate whether nutritional status may affect disease prognosis. Several assessment tools have evaluated and highlighted the potential beneficial impact of nutritional status on disease progression and patients' prognosis in both esophageal and pharyngeal cancers. Regarding esophageal cancer, CONUT, PNI, PG-SGA, and NRS-2002 are more commonly used, while albumin is also frequently evaluated. Regarding pharyngeal cancers, fewer studies are currently available. PNI has been evaluated, and its significance as a factor for shorter survival' times has been highlighted. The Comprehensive Nutritional Index has also been evaluated with positive results, as well as NRS 2002, GPS, and body-weight status. However, there is currently a lack of studies with an adequate number of women with cancer. An international literature gap was identified concerning follow-up studies with adequate methodology. Nutritional status may significantly affect disease progression and patients' survival, highlighting the significance of a great nutritional status in individuals with esophageal and pharyngeal cancers. Further large-scale and well-designed prospective surveys should be performed to verify the potential beneficial effects of adequate nourishment in people suffering from cancer of the esophagus and pharynx.