In hot and humid climates, a significant part of the energy is used to cool the building. There are several ways to reduce this air conditioning load, but one standout is through the selection and design of the right building envelope and its components. The thermal characteristics of the building envelope, in particular the thermal resistance of the insulation used, have an impact on the thermal and energy performance of building structures. Thermal conductivity, which indicates the ability of heat to move through a material given a temperature difference, is the primary factor affecting the performance of a thermal insulation material. Both temperature and humidity changes can affect a material’s thermal conductivity value, which can then change. In fact, due to the fluctuating ambient air temperature and solar radiation, thermal insulation in buildings is susceptible to significant and continuous temperature variations. Thermal insulation used in building walls and roofs helps to reduce the energy demand of the building. It improves thermal comfort and, if used correctly, reduces the operational cost of the building. The present study has focused on the effects of location and insulation material on the energy performance of a residential building by considering five climatic locations in the Kingdom of Saudi Arabia (KSA). Five commonly used insulation materials with different thermal characteristics, namely polyurethane board (PU), expanded polystyrene (EPS), glass wool (GW), urea-formaldehyde foam (UFF), and expanded perlite (EP), were analyzed under various climatic zones as per the Saudi Building Code 601/602. The selected cities were categorized based on cooling degree days (CDD) and outdoor dry bulb temperature (DBT) as hot, very hot, and extremely hot climatic zones. Insulation improves thermal comfort and, if used correctly, reduces running costs. Experiments were conducted to determine the thermal conductivity, and the energy simulation was performed by employing IES-VE software for various insulation options. The findings indicate that the location has a significant impact on the energy performance of the insulating materials. The energy saving potential of polyurethane board (PU) insulation is more attractive in cities with higher DBTs and CDDs than in cities with lower DBTs and CDDs. The benefit of installing insulation ranged from a 2 to 14% decrease in energy demand for the climate zones studied. The sensitivity analysis showed that the energy saving potential of the insulation materials is sensitive to the set-point temperature (ST) band. One of the most significant energy demands is the energy demand of residential buildings, which has economic and environmental impacts. According to statistics from the International Energy Agency (IEA), the residential sector uses 2142 Mtoe of the 9424 Mtoe total global energy demand . This coAn enormous amount of work has been carried out to reduce the impact of energy and natural resource consumption by buildings. Consequently, serious steps were taken to consider the design and operation of future building envelopes . Current2K/W, whereas those for Abha were in the range of 1.34 to 1.99 m2K/W [With regard to wall insulation, another comparative study of insulation materials in external walls was carried out by Axaopoulos et al. to investigate the difference between expanded polystyrene, extruded polystyrene, and mineral wool of various thicknesses. Mineral wool was found to be effective when compared with polystyrene insulation . Al-Sane99 m2K/W ,21,22. K99 m2K/W  used ins99 m2K/W  experime99 m2K/W . Alwetai99 m2K/W  numerica2K/W, as reported by Al-Sanea et al. [Densley Tingley et al. have examined the emissions caused by various kinds of insulation materials in buildings and found polystyrene to be the most favorable . Dicksona et al. . Alrashea et al. .A review of previous research and studies has shown that the thermal properties of insulation materials can change significantly as the operating ambient dry bulb temperature and humidity change. In Saudi Arabia, the cooling design dry bulb temperature typically surpasses 40 °C. The ambient dry bulb temperature and relative humidity (RH) are the significant factors affecting the thermal conductivity of insulating materials . Most thThe experimental investigations were conducted to determine the thermal characteristics of the studied insulation materials. The thermal conductivity of the insulation samples were measured under steady-state conditions using the heat flow meter that conforms to ASTM C518, JIS A1412, ISO 8301, and DIN 12667 standards ,35. The Building simulation tools have emerged to provide building professionals with a robust way to analyze building energy performance. They still encounter some criticism by many building scientists; these critiques lie in their approximation, flexibility, and integration with other engineering software . The stuThe computations are carried out employing a thermal balancing method that accounts for the concurrent interaction of model–building with external environmental factors to be assessed along with numerous loads on an hourly basis. It is simple to use, has a range of modules, and provides a comprehensive analysis of building performance. Several scholars have identified it as one of the most effective simulation software tools and have frequently employed it in their studies and analyses, according to the examined literature. Several researchers have compared the IES-VE simulation results to field observations and validated the software based on the degree of discrepancy in values in the range from 0 to 10% ,39. SeveThe International Weather for Energy Calculations 2.0 (IWEC2), ASHRAE, provided the climate data for the five cities. Climate Consultant software (version 6.0) is a graphic-based computer program developed by the University of California Energy Institute (UCEI), Berkeley, CA, USA. It is used to retrieve the data from the weather file. Sensible heat transmission through walls and opaque exterior surfaces  as well as transparent façade surfaces (glazed windows and skylights). Sensible and latent heat flows from ventilation/infiltration.Heat gains from people, illumination, and machinery that are sensible and latent.Direct power consumption for devices and lighting.The first stage in evaluating the building’s energy usage was to identify the various sources, modes, and power-consuming elements. The IES VE simulation takes into consideration the following sources, modes, and power-consuming components:The total energy required is determined as the sum of the cooling load, heating load, lighting load, and device load. The first three items in the list above help reduce the energy requirements of HVAC systems for cooling and heating. In cold-dominated climates, however, the proportion of heating demand to cooling load is relatively small (or negligible). As a consequence, the heating requirement was neglected when assessing the total energy requirement. Furthermore, as it is unaffected by changes in the choice of passive design, the equipment load remained constant throughout the study, while the cooling and lighting loads fluctuated (the lighting load varies when the glazing system changes). The simulation software for the present building used the following set of mathematical equations:Sensible heat flow by conduction through wall, roof, glass, partitions, ceiling, and floor ,42:SHconSensible heat flow by radiation from external opaque and transparent surfaces:Sensible and latent heat flows by ventilation/infiltration ,42:SH insulation. The energy saving potential due to the various insulation materials is attributed to the variations in thermal characteristics (as discussed above). There are certain operating conditions that influence the building’s energy demand, such as the set-point temperature (ST) and relative humidity (RH). Accordingly, a sensitivity analysis of these operating parameters was performed for insulation options as well as for the base case. For each option, the annual energy consumption was estimated by varying ST and RH, and the percentage saving with respect to the corresponding baseline energy consumption was obtained in each case for Tabuk region, as summarized in The thermal conductivities of the PU, EPS, GW, UFF, and EP insulations were 0.025 W/mK, 0.036 W/mK, 0.0315 W/mK, 0.0358 W/mK, and 0.044 W/mK, respectively.The insulated wall, irrespective of the type of insulation, reduced the annual energy demand by around 2 to 14% compared to the uninsulated wall of the building structure. The energy saving potential of the insulation materials significantly differed with the climatic conditions.The application of insulation could yield energy saving of 1.2%, 5.2%, 5.15%, 3.16%, and 13.6% in Abha, Dammam, Riyadh, Najran, and Tabuk, respectively.A sensitivity study on operational factors including RH and ST was used to validate the estimated energy saving potential and showed that it was relatively independent of RH and valid for the commonly used range of ST.The annual average indoor air temperature of the building was found to be 21.7 °C, 21.9 °C, 22.3 °C, 22.5 °C, and 23.2 °C for walls with PU, EPS, GW, UFF, and EP insulation, respectively.The results showed that while meeting the code requirement for an energy efficient envelope could result in a significant reduction in cooling energy demand, it actually increases the cooling demand in Abha, which represented hot regions.The difference in primary energy was not significant between glass wool (GW) and urea-formaldehyde foam (UFF) insulation.The polyurethane board (PU) insulation was found to be the most effective for the cities of extremely hot regions (Dammam and Riyadh), whereas expanded perlite (EP) insulation was efficient in hot climatic zones (Abha).This paper investigates the effect of location and insulation material type on thermal and energy performance of the buildings in Saudi Arabia. The findings can be summarized as follows:The outcomes of this research will be useful to engineers, policymakers, and designers, particularly in the application of thermal insulation materials for buildings in different climates of Saudi Arabia. The study could be applied to all locations falling under International Energy Conservation Code (IECC) climate zones 1, 2, 3A, and 3B. Future research could focus on the lifecycle cost (LCC), life cycle assessment (LCA), and indoor thermal comfort of different insulation materials. Different types of buildings, with varied window-to-wall ratios, heating/tropical environments, and other geographical locations are also subjects for additional research.


The short-term therapeutic success of radiofrequency ablation (RFA) in solid benign thyroid nodules is of great concern. The aim of this study was to investigate a new method, initial radiofrequency ablative ratio (IRAR) using contrast-enhanced ultrasound (CEUS), for predicting therapeutic success of RFA in solid benign thyroid nodules (BTNs) immediately and effectively after RFA.A total of 813 nodules in 776 patients with benign thyroid nodules were treated with RFA from January 2014 to August 2018, among which 120 patients (M:F=41:79) with 120 solid BTNs  were enrolled in our study according to the inclusion criteria. The IRAR was defined as the ablative volume ratio immediately after RFA displayed by CEUS. The therapeutic success was evaluated at the 6-month follow-up. The relationship between the IRAR and volume reduction ratio (VRR) at 6-month was analyzed. The marginal regrowth of solid BTNs was also examined by CEUS at the 6 and 12 months of follow-up.P < 0.001) at 6 months after RFA. There was a tendency to achieve therapeutic success  when the IRAR exceeded 75%, and marginal regrowth was also relatively slow within 12 months after a single session treatment. No significant correlation between IRAR and VRR of small nodules was found. In conclusion, IRAR is significantly and positively correlated with VRR, which may indicate therapeutic success when it exceeds 75%.In medium and large nodules, the IRAR was significantly and positively correlated with VRR (r= 0.69, CEUS can be used to accurately quantify the IRAR, which is positively correlated with the VRR. Moreover, the IRAR may be used as a parameter to predict the short-term therapeutic success of RFA in solid BTNs. Imaging-guided thermal ablation (IGTA) is commonly performed in clinical therapy and has been proposed for benign thyroid nodule (BTN) treatment –3. AmongHowever, for solid BTNs, the accurate quantitative ablation range immediately after the first single session of RFA treatment to predict short-term therapeutic success is of great concern since therapeutic success has been used as an indicator of RFA success during the follow-up period , 16, 17.Contrast-enhanced ultrasonography (CEUS) is a widely used technique in recent years that is thought to help clarify the boundary between the ablated area and the viable area. We hypothesized that an accurate quantitative initial radiofrequency ablative ratio (IRAR) determined using CEUS could predict therapeutic success after RFA during short-term follow-up and possibly further predict the time range for additional ablation.The purpose of this study was to determine the IRAR (CEUS quantification) threshold for predicting therapeutic success by evaluating the correlation between the IRAR and VRR and to provide a possible time range for the additional ablation of solid BTNs.This retrospective study was approved by the Chinese PLA General Hospital Ethics Committee (S2019-211-01), and patient consent was waived.A total of 813 nodules in 776 patients with BTNs were treated with RFA from January 1, 2014, to August 31,2018. According to the inclusion and exclusion criteria, 120 nodules from 120 patients were selected  were measured before RFA. For each nodule, the volume was calculated using the following equation: V=πabc/6  , 18, 19.All nodules were confirmed to be benign by analysing the results of at least two FNA biopsies. No intravenous sedatives or analgesics were used preoperatively or intraoperatively. The patients were administered local anaesthesia with 2% lidocaine at the puncture site and a thyroid anterior capsule. To avoid the chance of thermal injury, hydrodissection was necessary if the distance between the nodule and the carotid artery, internal jugular vein, recurrent laryngeal nerve, trachea or oesophagus was less than 5 mm. Under continuous US tracing, the trans-isthmic approach or direct nodule puncture approach  and the CEUS examination (Siemens Acuson Sequoia 512 Ultrasound System with a 15L8W linear array transducer) was performed immediately after RFA to observe the blood supply in the ablation area and to ensure that the ablation was as complete as possible because unablated nodule portions with vascularity have considerable potential for regrowth on follow-up. However, colour Doppler US is not sufficiently sensitive to detect small blood vessels and slow blood flow . To overThe follow-up US examination was performed within 1 to 3 months postoperatively, and the second and third follow-up examinations were performed at 6 and 12 months after the single RFA treatment session. During the 12-month follow-up period, careful examination was required for early signs of nodular regrowth , including a thickness of viable tissue within the nodules exceeding 10 mm on CEUS. Regrowth was defined as an increase in nodule volume of 50% compared to that at the previous examination , 25. CEUP value less than 0.05 indicated a significant difference.The results were analysed by SPSS, version 22 . Continuous variables are reported as the mean ± SD with the range. The relationship between the IRAR and VRR (at the 6-month follow-up) was analysed by Pearson correlation analysis. A The baseline characteristics of the solid BTNs and the treatment characteristics of the patients, such as the ablation duration, energy and power, are summarized in The mean IRAR was 82.98 ± 18.23% among all nodules, and the mean IRAR of small nodules was greater than those of medium and large nodules. Correspondingly, the VRR of small nodules at 6 and 12 months after RFA was greater than those of medium and large nodules. In brief, for the same duration of volume reduction, nodules with a smaller initial volume showed a higher VRR. The initial volume, IRAR, and VRR during the follow-up period are summarized in P < 0.001) would reach 50% at 6 months after operation. IRAR cannot be used as a quantitative indicator for predicting the therapeutic success of solid BTNs radiofrequency ablation. The therapeutic success is very important for the patient’s postoperative management. Lim et al. and Valcavi et al. reported the recurrence rates after RFA (5.6%) and laser ablation 9%) , 26. All% , 26. AThe VRR was related to the initial nodule volume , 5, 13. The IRAR and VRR are closely related to the ablation equipment or technical factors . InternaThe IRAR we obtained was higher than that of the results reported by Sim et al. , which wThe limitations of this study must be taken into account. First, we recognize that the sample sizes in the different subgroups were relatively small, and that additional data are required to adequately assess the correlation between the IRAR and therapeutic success in solid BTNs. Another limitation was the retrospective design of this study and its performance at a single centre. Future prospective multicentre and/or multinational studies are necessary to confirm our results.In conclusion, CEUS can be used to accurately quantify the IRAR, which is positively and highly correlated with the VRR. If the IRAR exceeds 75%, therapeutic success may be achieved. By considering the nodule volume and the IRAR, the follow-up interval can be more systematically determined, and repeat ablation can be planned based on the patient’s symptoms or intentions if marginal regrowth occurs.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This retrospective study was approved by the Chinese PLA General Hospital Ethics Committee (S2019-211-01), and patient consent was waived. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.YZ and ZJ contributed equally to this work. YL and MZ contributed equally to this work. YL: conceptualization, methodology, supervision, and review and editing MZ: methodology, validation, supervision, and review and editing. YZ: methodology, formal analysis, data curation, original draft, and review and editing, and visualization. ZJ: formal analysis, data curation, original draft, and review and editing. Visualization: LZ: formal analysis, data curation, visualization. FX: formal analysis and data curation. QS: formal analysis, data curation, and original draft. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


When the analysis was repeated in each component of frailty, the highest quartiles of ucOC/OC had the tendency of association with “slow walking speed” and “low activity.” Our findings demonstrated the association between vitamin K insufficiency and frailty in the elderly population. Our analysis also suggests that vitamin K insufficiency could be associated with selected components of frailty.Frailty is the state of having a reduced ability to recover from stress. Intervention in frailty is important for fulfilling healthy longevity. Vitamin K is a fat-soluble vitamin contained in vegetables and fermented foods. Although vitamin K is shown to be associated with several age-related diseases, studies on the association of vitamin K intake and frailty in the elderly population are limited. In the present study, a total of 800 community-dwelling older adults (mean age = 75.9) were recruited for a comprehensive geriatric health examination, including frailty evaluation based on the Japanese version of the Cardiovascular Health Study criteria. Serum concentrations of total osteocalcin (OC) and undercarboxylated osteocalcin (ucOC) were measured. The ratio of ucOC and OC (ucOC/OC), which reflects vitamin K insufficiency, was calculated for each participant, and the values were divided into quartiles. A binary logistic regression analysis was performed to evaluate the risk of frailty for each quartile of ucOC/OC, with the lowest quartile as the reference. Significant association of frailty and the highest quartile of ucOC/OC was found with the odds ratio of 2.49 ( Vitamine (GGCX) . Substrae (GGCX) , matrix e (GGCX) , and oste (GGCX) . To datee (GGCX) . The late (GGCX) .Other than its clinical role in blood coagulation, vitamin K status is also associated with age-related diseases including osteoporosis  and osteSeveral epidemiological studies showed that frailty could be associated with the dietary pattern. Mediterranean diet was associated with the decreased risk of frailty . Intake In 2020, a total of 800 people (mean age = 75.9) were recruited as a follow-up study of the baseline examinations conducted from 2017 to 2019 by mailing community-dwelling older adults randomly from the Basic Resident Register of the Itabashi district in metropolitan Tokyo. Among them, 88.8% (710 people) were females. They were invited to a comprehensive geriatric health examination, including a frailty evaluation and blood test. Information on past medical history and dietary intake is obtained by using a self-reporting questionnaire. Grip strength and walking speed were measured by the staff of the Tokyo Metropolitan Institute of Gerontology. For the measurement of walking speed, participants were asked to walk for 11 m, and the walking time required for the 5 m in the middle of the way was then measured. Frailty was evaluated by the Japanese version of the Cardiovascular Health Study criteria . The fivThe serum ucOC/OC values are divided into quartiles . Descriptive statistics were used to compare patients’ characteristics according to the levels of ucOC/OC using one-way analysis of variance for continuous variables and a chi-square test for categorical variables. Binary logistic regression analysis was performed to evaluate the association of frailty with the following variables: age (continuous), sex (binary), body mass index , hypertension (binary), stroke (binary), heart disease (binary), diabetes (binary), dyslipidemia (binary), osteoporosis (binary), smoking status , ucOC/OC , and dietary intake . Components of dietary intake used for the analysis include meat, fish, eggs, soybean products, milk, cheese, potatoes, vegetables, fruits, seaweeds, and “oils and fats.” Vegetables are specified to be dark-colored vegetables, including carrots, spinach, pumpkins, and tomatoes. “Oils and fats” indicate stir-fried foods, butter, and margarine. Dietary intake was positive when the frequency of intake was nearly every day. In the chi-square test, the specific intake of “fermented soybeans,” one of the soybean products, was included in the analysis. In the case of fermented soybeans, the frequency of intake of more than 3 days a week was defined as positive. Binary logistic regression analysis was repeated to evaluate the association of each component of frailty  with the same variables in the analysis of frailty itself. IBM SPSS Statistics version 25 software  was used for all statistical analyses.p < 0.001 in chi square test). Since the fermented soybeans contain a high amount of vitamin K2 . These results indicated that older age, hypertension, diabetes, osteoporosis, and vitamin K insufficiency are associated with frailty. In addition, the body mass index between 25 and 30 and the positive smoking status tended to correlate with frailty  of ucOC/OC with the lowest quartile (Q1) as the reference were significantly associated with frailty . The odd frailty .p value 0.092) and “low activity”  with adjustment for age, sex, body mass index, hypertension, stroke, heart disease, diabetes, dyslipidemia, osteoporosis, smoking status, and dietary intake , weakness (grip strength of less than 26 kg in men or less than 18 kg in women), exhaustion (feeling of tiredness without a reason in the past 2 weeks), slowness , and low activity . When the analysis was repeated with each component of frailty, the highest quartile of ucOC/OC had a tendency of association with “slowness” (OR 1.80, 95% CI 0.91 to 3.56, and y intake . The resIn the present study, we demonstrated the association of vitamin K insufficiency as evaluated by the serum ucOC/OC ratio with frailty in a community-dwelling older adult population. Furthermore, our analysis suggests that vitamin K insufficiency tended to be associated with slow walking speed and low activity.In the epidemiological studies evaluating vitamin K insufficiency, vitamin K status has been estimated by food-frequency questionnaires , plasma A possible association with vitamin K insufficiency and slow walking speed was in line with previous reports . The rep. A study using rat models demonstrated that vitamin K decreased depression-like behavior in the forced swim test and increased the score of the social interaction test (We proposed another possible association between vitamin K and “low activity.” The low activity can be caused by a sedentary lifestyle and decreased physical performance. It can be hypothesized that vitamin K may affect lifestyle by regulating psychological aspects. In an old study using vitamin K-deficient rats by administrating warfarin, hypoactivity and lack of exploratory behavior were observed . A studyion test , which sion test . In miceWe noticed that there are several limitations to this study. First, the majority of the population was females in our analysis. This problem could be overcome to some extent by using the statistical method of adjusting sex. Second, we did not have detailed information on the medications that potentially affected the function of vitamin K, such as anticoagulants. Therefore, our results may also include the effect of suppressive vitamin K function by anticoagulants on frailty. Third, we did not have information on the medication’s effect on bone turnover, which may affect the concentration of OC. Our analysis could be less susceptible to the absolute amount of OC by calculating the ratio of ucOC to OC. Since our study is an observational study, we could not discuss the cause-effect relationship between vitamin K and frailty. Considering the importance of intervention to frailty for fulfilling healthy longevity, we hope that our study could be one of the backgrounds to prompt clinical intervention studies clarifying the effect of vitamin K supplementation on the reversing frail state.In summary, the present study demonstrated the association between vitamin K insufficiency and frailty in the older adult population. Our findings could be a clue to designing further studies on how vitamin K functions in frailty and its underlying conditions.


Many patients with gastric cancer are at a locally advanced stage during initial diagnosis. TNM staging is inaccurate in predicting survival. This study aims to develop two more accurate survival prediction models for patients with locally advanced gastric cancer (LAGC) and guide clinical decision-making.We recruited 2794 patients diagnosed with LAGC (2010–2015) from the Surveillance, Epidemiology, and End Results (SEER) database and performed external validation using data from 115 patients with LAGC at Yantai Affiliated Hospital of Binzhou Medical University. Univariate and multifactorial survival analyses were screened for meaningful independent prognostic factors and were used to build survival prediction models. Concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were evaluated for nomograms. Finally, the differences and relationships of survival and prognosis between the three different risk groups were described using the Kaplan–Meier method.Cox proportional risk regression model analysis identified independent prognostic factors for patients with LAGC, and variables associated with overall survival (OS) included age, race, marital status, T-stage, N-stage, grade, histologic type, surgery, and chemotherapy. Variables associated with cancer-specific survival (CSS) included age, race, T-stage, N-stage, grade, histological type, surgery, and chemotherapy. In the training cohort, C-index of nomogram for predicting OS was 0.722 . In the external validation cohort, C-index of nomogram for predicted OS was 0.728 (95% CI:0.672–0.784) and CSS was 0.727 (95% CI:0.668–0.786). The calibration curves showed good concordance between the predicted and actual results. C-index, ROC, and DCA results indicated that our nomograms could more accurately predict OS and CSS than TNM staging and had a higher clinical benefit. Finally, to facilitate clinical use, we set up two web servers based on nomograms.The nomograms established in this study have better risk assessment ability than the clinical staging system, which can help clinicians predict the individual survival of LAGC patients more accurately and thus develop appropriate treatment strategies. Gastric cancer is one of the most common malignancies worldwide. According to GLOBOCAN 2018, it ranks fifth in incidence and third in overall mortality among all cancers, after lung and colorectal cancers , 4. SurgThe American Joint Committee on Cancer (AJCC) staging system is a common tool used clinically to predict disease progression and design treatment strategies , 15. HowNomogram is a reliable and convenient prognostic prediction tool. It can quantitatively predict the prognosis of each cancer patient based on multiple prognostic factors to provide more effective individualized medical treatment, and it is widely recognized and used in the international arena , 22. ForOur study was based on data information from the Surveillance, Epidemiology, and End Results (SEER) database and Yantai Affiliated Hospital of Binzhou Medical University (YAHBMU) for LAGC patients. The SEER database is a National Cancer Institute (NCI)-funded project covering approximately 30% of the U.S. population and contains data information from 18 cancer registries with large sample sizes, wide population coverage, high data accuracy, and multicenter and multi-regional registries of case samples advantages .We collected data information on 2794 (2010–2015) LAGC patients from SEER database. Inclusion criteria were as follows: (i) gastric cancer patients with clinical stage T1-2N+M0 and T3-4N0/+M0; (ii) patients with no other confirmed tumors other than LAGC; (iii) complete clinical and pathological data; (iv) complete follow-up information. Exclusion criteria were as follows: (i) patient age < 18 years at diagnosis; (ii) unknown data on race, grade, surgery and marital status; and (iii) follow-up time of 0 and unknown. We assigned approximately 70% of these LAGC patients  to the training group, and the remaining 30% (n = 848) to the internal validation group using R software. If the sample size of the missing value in the database was less than 5% of the total number of people, it will be deleted. We also collected data information of 115 (2014–2018) LAGC patients from YAHBMU, which served as an external validation cohort. Inclusion and exclusion criteria were as above. Follow-up visits were conducted through direct contact with patients or telephone conversations. The follow-up ended on June 30, 2022. This study was approved by the YAHBMU Ethics Committee.This study was designed on the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) . The endWe used the X-tile software  to divide the ages into three groups in the training set. The scores of each independent prognostic factor were summed to obtain the total risk score of LAGC patients. Using the best cut-off value of the total risk score determined by X-Tile software (version 3.6.1), LAGC patients were classified into high-, intermediate-, and low-risk groups. Kaplan–Meier curve was employed to assess OS and CSS of LAGC patients.The obtained data were statistically analyzed using SPSS software version 22.0 and R software version 4.1.2. The data were analyzed by the χ2 test or Fisher’s exact probability method. The Kaplan–Meier method was utilized to plot the survival curves, and the log-rank test was used to compare the survival rates. After setting the seed number, LAGC patients were randomly divided into training and internal validation groups in the ratio of 7:3 using the “caret” package in R software. The training cohort was used to determine the independent prognostic factors of LAGC patients and create prognostic nomograms, while internal and external validation cohorts were used to test the accuracy of the nomogram. Univariate and multifactorial COX regression analyses were employed to identify independent prognostic factors for LAGC. After calculating the variance inflation factor (VIF), the VIF values of each covariate were less than 4, suggesting that the multicollinearity between variables is not significant. Based on univariate and multifactorial regression analyses, clinical and pathological characteristics that could be used as independent prognostic factors were included, and “rms,” “foreign,” and “survival” packages of R software were used to construct nomograms of LAGC patients. The degree of differentiation was the ability to distinguish the proposed model from conventional AJCC staging and was measured in terms of C-index and the area under the receiver operator characteristics curve (AUC). The C-index and AUC range from 0.5 to 1. The closer the C-index and AUC values were to 1, the better the model’s differentiation was. A calibration curve was also used to measure the closeness of the predicted risk to the actual risk. The vertical coordinate of the curve was the actual survival rate of LAGC patients, and the horizontal coordinate was the survival rate predicted by the nomogram. By observing the degree of deviation of the curve from the diagonal line, it was possible to determine whether the constructed prediction model could accurately predict OS and CSS at 1, 3, and 5 years. Finally, DCA was used to verify the clinical validity. The difference was indicated as statistically significant at p < 0.05.This study collected information on 2794 eligible LAGC patients  from SEER database and external validation of 115 eligible LAGC patients from YAHBMU. Screening details and demographic characteristics are shown in As listed in The risk ratios and univariate and multivariate Cox risk models are shown in The best cut-off values were obtained using X-Tile software on the total scores of LAGC patients, which were 210 and 308 for OS and 217 and 309 for CSS. Therefore, LAGC patients were classified into the low-risk group (43–210), the medium-risk group (211–308), and the high-risk group (309–458) for OS. In addition, LAGC patients were classified into the low-risk group (44–217), the medium-risk group (218–309), and the high-risk group (310–449) for CSS. Meanwhile, X-tile classifies patients’ ages into three groups: 18–66, 67–80, and 80–100. https://houchong.shinyapps.io/lagcoverall/) and CSS (https://houchong.shinyapps.io/lagcspecific/) of LAGC patients. By inputting information about LAGC patients, the intertemporal survival probability of patients can be easily predicted, which can better assist clinical efforts.Based on the nomograms we created, we developed two web servers to predict the OS (Due to early gastric cancer patients lacking obvious clinical symptoms, most gastric cancer patients are at locally advanced stages at the time of diagnosis. Currently, clinicians usually evaluate cancer through TNM system, which is generally regarded as the gold standard for diagnosis and treatment and the benchmark for prognosis . Given tThe nomogram is based on multifactorial regression analysis, which can predict certain clinical outcomes or the probability of a certain type of event, and its analysis results are graphical and visualized, which can help clinicians make clinical decisions based on the prognosis predicted by the model . In thisWhen performing prognostic factor analysis, we discovered that elderly patients tend to have a poorer prognosis, which is also true in other cancers. This may be linked to the weaker immune system of the elderly, the weakened reserve function of many of their own organs, and the possibility of comorbidity with multiple diseases. Older patients with gastric cancer are less likely to receive treatment than younger patients because, in contrast to the latter, the former is more likely to have postoperative complications and poor compensatory capacity, eventually leading to poor tolerance of the surgery , 28. OneSurgery combined with adjuvant chemotherapy is currently an important part of the standardized treatment system for gastric cancer, and aggressive treatment is of great clinical significance in improving the quality and prolonging the survival time of patients . Many paNotably, several significant advantages of our study should be considered. First, this study establish prognostic nomograms for predicting OS and CSS in LAGG patients, and the results of internal and external validation have revealed the reliability and accuracy of nomograms. Second, this study includes other risk factors that affect the prognosis of LAGC patients in addition to TNM stage and classifies patients into three risk groups—high, medium, and low—to provide more information for clinical work. Also, LAGC patients can obtain a total score, find their own risk group according to the nomogram, and then assess their future survival, which has strong clinical guidance. For LAGC patients with high scores and risk, clinicians can make more timely therapeutic interventions and treatment plan adjustments to improve their prognosis. Third, our models can be used to improve the AJCC TNM staging system or as a complementary version. C-index and AUC values of the nomograms for two different study endpoints, OS and CSS, are higher than those of TNM staging in training and two validation groups, indicating that prediction models have better accuracy in predicting patient survival time. The calibration curves also showed a high degree of agreement between predicted and actual observed results, reflecting the reliability of prediction models. Compared with conventional TNM staging system, the clinical benefit of the nomogram was better, as illustrated by DCA curve, which also reflects the superiority of the nomogram. Fourth, based on the nomogram model, we built two network calculators. The ability to predict OS and CSS of LAGC patients more easily and intuitively by inputting patient prognosis-related information provides a convenient tool for clinicians. Finally, Our study can add more useful information to the studies of survival analysis of LAGC. Previous studies have been relatively restrictive regarding the conditions of LAGC patients, such as non-elderly LAGC patients undergoing gastrectomy, LAGC patients over 75 years of age, and patients with locally advanced gastric signet-ring cell carcinoma , 41–43. Helicobacter pylori infection, patients’ body mass index, neurological or vascular or lymphatic vascular invasion, which are also are important factors affecting the prognosis of cancer patients. The absence of such factors may weaken the predictive power of the prognosis of LAGC patients. Finally, the data used to develop and validate the nomogram came only from our hospital and the SEER databases. For example, in our hospital, the patients are only Asian, which inevitably causes some bias in external validation regarding race. Although study results suggest that our nomograms have good predictive accuracy, larger as well as multicenter clinical trials in different countries are required to assess their performance.However, there are some limitations to our study. First, data in SEER database being retrospective information may have led to a potential risk of selection bias during the construction of prediction models. Second, the information in SEER database is incomprehensive, such as the lack of information on cancer patients from other countries and the lack of some other prognostic risk factors associated with survival, such as smoking history, alcohol consumption, We constructed nomograms that can predict OS and CSS at 1, 3, and 5 years in patients with LAGC and determined the reliability and accuracy of the models through multiple validations. Compared with the AJCC TNM staging, our nomograms performed better in predicting prognosis and can be used as a useful tool to assess the prognosis of LAGC patients, thus contributing to clinical decision-making and individualized treatment planning.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Yantai Affiliated Hospital of Binzhou Medical University Ethics Committee. The ethics committee waived the requirement of written informed consent for participation.CH and FY: conception and design. CH and FY: development of methodology. CH: acquisition of data. FY: analysis and interpretation of data. CH and FY: writing, review, and/or revision of the manuscript. CH, FY, and YL: administrative, technical, or material support. CH and FY: study supervision. All authors participated in the writing of the final manuscript and approved the final submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This study aimed to investigate the association between the alternative healthy eating index-2010 (AHEI-2010) with cognitive function and the mediating role of depressive symptoms in older adults using the data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). The AHEI-2010 was calculated from NHANES individual food data and Food Patterns Equivalents Database (FPED) diet data. Cognitive function was assessed by the Consortium to Establish a Registry for Alzheimer’s disease , Word Learning sub-test, digital symbol substitution test , animal fluency test , and the comprehensive z-score . A weighted multiple linear regression model was used to explore the relationship between AHEI-2010 and cognitive function, and Karlson–Holm–Breen (KHB) method was used to explore the mediating effect of depressive symptoms. A total of 2644 participants were included in this study. Participants with higher AHEI-2010 scores were more likely to have higher scores in DSST, AFT, and comprehensive z-score compared with the lowest quartile. Depressive symptoms play a significant mediating role between AHEI-2010 and cognitive function. The proportion of mediating in CERAD, DSST, AFT, and comprehensive z-score was 14.14%, 9.10%, 9.15%, and 10.47%, respectively. This study found that higher dietary quality was associated with better cognitive function. In addition, depressive symptoms may be an important pathway linking diet and cognitive function. Cognitive decline is a feature of the aging process, which is characterized by the impairment of intellectual abilities such as memory, reasoning, executive function, and information processing speed . There aThe Alternative Healthy Diet Index (AHEI) is a measure of diet quality and represents the extent to which overall healthy diet patterns are followed, which provides better recommendations to improve health risk factors as well as greater predictive power for chronic disease relative to the Healthy Diet Index (HEI) . So far,Several studies reported that lower dietary quality was associated with a higher risk of depression ,12,13,14In conclusion, the above evidence suggests that depression may be in the causal chain between diet and cognitive function. However, so far, no study has explored whether depression plays a mediating role in the relationship between dietary quality and cognitive function. Therefore, the purpose of this study was to use the data of the National Health and Nutrition Examination Survey (NHANES) and the Food Patterns Equivalents Database (FPED) diet data to analyze the relationship between AHEI-2010 and cognitive function and further investigate whether this relationship was mediated by depressive symptoms.https://www.cdc.gov/nchs/nhanes/index.htm) (access date: 11 July 2022). NHANES, an ongoing biennial cross-sectional survey administered by the Centers for Disease Control and Prevention, aimed to assess the health and nutritional status of adults and children in the United States. Participants were selected through a complex, multistage, probabilistic sampling design, so the sample represents the non-institutionalized U.S. civilian population. In this study, we combined data from two NHANES cycles (NHANES 2011–2012 and 2013–2014), which consist of a series of cognitive function tests. A total of 19,931 participants took part in the survey between 2011 and 2014. Our analysis was limited to adult participants aged 60 and over who participated in the cognitive function survey . Participants with missing dietary data were excluded (n = 209). Those who did not complete the cognitive function test (n = 698) were also excluded. In addition, participants with missing covariates such as race, education status, smoking, and chronic diseases were also excluded (n = 81). Finally, 2644 older adults aged 60 and over were included in the analysis , created in 2002. Previous studies showed that the AHEI-2010 had a better predictive ability for chronic disease relative to the HEI . AHEI-20Cognitive function was assessed by the Consortium to Establish a Registry for Alzheimer’s disease (CERAD) Word Learning subtest, Animal Fluency Test (AFT), and Digital Symbol Substitution Test (DSST). The CERAD assessed immediate and delayed learning ability of new verbal information (memory sub-domain) and consisted of three consecutive learning trials and a delayed recall. The AFT examined categorical verbal fluency, a component of executive function. Participants were asked to name as many animals as possible in one minute. The DSST, a performance module from the Wechsler Adult Intelligence Scale, relied on processing speed, sustained attention, and working memory. Participants had two minutes to match the symbols corresponding to numbers. The score was defined as the total number of correct matches. In order to reflect the information on the overall cognition, after the standardization of the three cognitive scores, the average value was calculated as the composite z-score, and the influence of AHEI on global cognition was analyzed.A patient health questionnaire, a nine-item depression screening tool, was used to determine the frequency of depressive symptoms in the past 2 weeks. The answer categories of the nine items “none at all”, “a few days”, “more than half of the days”, and “almost every day” were given a score ranging from 0 to 3. The total score is the sum of the scores of nine items. The total score ranges from 0 to 27.2 (Kg/m2), and according to WHO criteria [2), normal weight (18.5–24.9 Kg/m2), or overweight (≥25 Kg/m2). Diabetes, hypertension, heart disease, and stroke were defined based on self-reported status from diagnosis by doctors and were defined as yes or no.Age, gender , race , education status , marital status , smoking status , alcohol drinking status (yes or no). Body mass index (BMI), diabetes, heart disease, and stroke. BMI was defined as weight/heightcriteria , particiAll data were analyzed by Stata15.0  software version. Considering the complex sampling design of NHANES, a new sample weight  was created according to the analysis guidelines of NHANES.The basic characteristics of continuous variables were described by mean and standard deviation, while classified variables were described by percentage. Kruskal–Wallis test or one-way analysis of variance (ANOVA) was used to analyze the difference between continuous variables. The Chi-square test was used to analyze the differences between classified variables.p-value were two-sided; p < 0.05 was considered statistically significant.The weighted multiple linear regression was used to evaluate the relationship between AHEI-2010 and cognitive function. A linear regression model based on Karlson–Holm–Breen (KHB) method  was usedp < 0.001). With the increase in the AHEI-2010 quartile, the number of people drinking alcohol and suffering from hypertension increased, but the number of strokes decreased. In addition, the DSST and AFT scores of the highest AHEI-2010 quartile were significantly higher than those of the lowest quartile. There was no significant difference in age, BMI, and heart disease.p trend < 0.01). In the fully adjusted model, the highest quartile was still significantly correlated with DSST, AFT, and comprehensive z-scores. In addition, the linear trend of AHEI-2010 in DSST, AFT, and comprehensive z-scores still existed (p trend < 0.01). Depressive symptoms were significantly negatively correlated with all cognitive function measures, and no significant correlation between AHEI-2010 and CERAD was found in all models.The results of the mediation analysis are shown in This cross-sectional study used the NHANES data from 2011–2012 and 2013–2014 to analyze the relationship between AHEI-2010 and cognitive function and the mediating role of depressive symptoms and found that higher dietary quality was associated with better cognitive function among older adults, especially in terms of processing speed and executive function. In addition, depressive symptoms play a partial mediating role in the relationship between AHEI-2010 and cognitive function.Our findings on the relationship between AHEI-2010 and cognitive function are consistent with previous studies. For example, in two international parallel trials, ONTARGET  and TRANSCEND (Telmisartan Randomized Assessment Study in ACE Intolerant Subjects with Cardiovascular Disease), 27,860 participants were followed up for 56 months and found that higher dietary quality was associated with a reduced risk of cognitive decline . A folloThe effect of diet quality on cognitive function may be partly mediated by depression. We found that the AHEI-2010 score was significantly negatively associated with depressive symptoms, and so was the relationship between depressive symptoms and cognitive function. In the analysis of AHEI-2010 components, we found that the intake of vegetables, fruits and nuts, and legumes recommended by AHEI-2010 was associated with better cognitive function, while the intake of sugary drinks and sodium was the opposite. At present, there is evidence that AHEI-2010 restricted components, especially the intake of sugary drinks, red meat, and processed foods, which might increase the risk of body inflammation and change intestinal microflora. In turn, they might have negative effects on the brain and increase the risk of developing depression ,24,25,26Meanwhile, some cross-lagged analyses in older adults have shown that depressive symptoms may be a risk factor for cognitive decline ,16,17. TBased on the above evidence, it can be seen that diet quality may affect cognitive function through depression symptoms. Therefore, active dietary intervention in people with depressive symptoms in later life may help maintain better cognitive function and delay the onset of dementia. Even a small reduction in the risk of dementia could have large health benefits for the public due to the predicted rapid increase in the number of people with dementia in the future.Our study has several advantages. To our knowledge, this is the first time to explore the mediating effect of depressive symptoms on the association between dietary quality and cognitive function. Second, the sample size is large enough, and because the quality of the NHANES survey is very high, the representativeness of the sample is pretty good, which can be extended to the whole US population. However, the disadvantages of the article should not be ignored. First of all, this is a cross-sectional study in which causality cannot be determined. Second, there may be recall bias in the process of self-reported dietary data collection.In conclusion, the results of this study suggest that a better quality of diet may reduce the degree of depressive symptoms and thus maintain better cognitive function. It is worth noting that dietary quality is an important and effective means of intervention, which is of great significance for the prevention of age-related cognitive decline and even dementia.


Tuberculosis (TB) in prisons usually occurs at higher rates than in the general population, especially in developing countries. TB has been reported as the most common cause of death among prisoners. Studies have shown limitations for early detection of TB in prisons that seem to result from mistaken concepts about TB, delayed diagnosis mainly due to the naturalization of lack of healthcare for this populationA scoping review was performed using the methodology of the Joanna Briggs Institute to assess “What are the scientific evidences on the epidemiology of TB in the prison system?”. Then, a meta-analysis was performed to assess the prevalence of TB (active and latent) TB in prisoners. The results are presented as prevalence, in percentage, through random effects models, with a confidence interval of 95%.Regarding active TB, the results of the metanalysis showed that countries with a high burden of TB had a prevalence of 3.54% , countries not considered to be high burden TB countries had a prevalence of 1.43% . Latent TB had a prevalence of 51.61%  in high TB burden countries and a prevalence of 40.24%  in countries with low TB burden. In terms of development, in low- and lower-middle-income countries, the prevalence of active TB was 3.13%  and in high- and upper-middle income countries the prevalence was 2.25% . The prevalence of latent TB in high- and middle-income countries was 43.77%  and of 49.42%  in low and lower middle-income countries.Our analysis suggests that TB, and probably other infectious diseases, find fertile ground in prisons where previous acquire social disadvantages seem to thrive—therefore, TB in prisons is a global public health problem and effective strategies are needed to control the disease are needed targeting the prison environment, including rapid health assessments to understand each context and to implement tailored and precision interventions.The online version contains supplementary material available at 10.1186/s12879-022-07961-8. Tuberculosis (TB) is a communicable disease and one of the ten leading causes of death worldwide. It is also the leading cause of death by a single infectious agent, surpassing HIV .TB in prisons usually occurs at higher rates than in the general population, especially in developing countries. TB has been reported as the most common cause of death among prisoners . A disprDuring incarceration, prisoners face living conditions, such as crowding, absent or precarious basic sanitation and housing infrastructure, malnutrition, poor ventilation, deficient lighting, illicit drug use and difficulty in accessing health services, that make the prison system a potential TB-transmitting (and aggravating) environment –5.Studies have shown limitations for early detection of TB in prisons that seem to result from mistaken concepts about TB, delayed diagnosis mainly due to the naturalization of lack of healthcare for this population, interpretation of prisons as places of "death" and "suffering" and, in some situations, deprivation of the right to health for detainees due to their position before society , 7. ThesTB in prisoners is, thus, a major public health concern that contributes to the dissemination of TB and the perpetuation of its effects not only in this population but in society in general.Several types of reviews have addressed the issue of TB in prisoners  –19. NeveWe conducted a scoping review (SR) to address the review question “What are the scientific evidences on the epidemiology of TB in the prison system?”. For the purposes of this SR, we defined epidemiology as events, states, health processes and factors involving TB in prisoners described as incidence, prevalence, associations, comparisons, predictions, correlations, descriptions, risks, trends or probabilities resulting from studies.The large number of prevalence results found led us to carry out the meta-analysis reported in this paper.https://osf.io/vn2cw/.A SR was performed using the methodology of the Joanna Briggs Institute .The prot; Latin American and Caribbean Literature in Health Sciences (LILACS); Scopus (Elsevier) and Scientific Electronic Library Online (SciELO) using the following search terms and keywords: Tuberculosis, Kochs Disease, Koch's Disease, Koch Disease, Mycobacterium tuberculosis Infection, Mycobacterium tuberculosis Infections, Prisons, Prison, Penitentiaries, Penitentiary, Prisoners, Prisoner, Prison inmate. The search strategies used in each database are detailed in Additional file 1.Databases were searched in June 2021. No time limit was applied. We searched Medical Literature Analysis and Retrieval System Online (MEDLINE/PubMed)We adopted the strategy: Population (P), Concept (C), Context (C)  as definStudies that presented cases of TB in all clinical forms  from A-15 to A-19 according to the International Classification of Diseases version 10—ICD-10 were included .We excluded publications that investigated other infectious diseases and that had no data on TB, that addressed the relationship between TB and drug use, studied immigrant population who were also deprived of liberty, TB coinfection with HIV and/or Hepatitis C; molecular epidemiology of TB, TB lineage variation; TB after leaving the prison system; drug resistant TB; sensitivity testing methods; performance of scores for TB screening; case studies; cost of TB tests in prisons; prisoners of war with TB; summaries of official TB control consensus documents in the prison system; and qualitative studies.References retrieved from databases were assessed independently (title and abstract) by two reviewers (AP and DS), after removal of duplicates. Disagreements were resolved by a third reviewer (IF). Publications eligible for full-text reading were again assessed independently by two reviewers (AP and DS).Data extraction was conducted by AP and DS using an adapted version of the form of the JBI  model acIncluded studies were divided into the following categories: prevalence, incidence, associated factors, treatment outcomes, environmental factors and effects of prevention programs. In this paper, we report only on included studies that presented prevalence data. All studies addressing prevalence of TB were assessed in terms of quality and risk of bias and subjected to meta-analysis.We used the JBI critical appraisal tools for prevalence studies and for cross-sectional studies . CriticaEach checklist consists of eight  or nine questions , with four options of answer: yes; no; unclear and not applicable. To decide on the quality of the studies and to define which were low, medium or high quality we attributed a score to each item, being, 2 for yes or not applicable, 1 for unclear and 0 for no. The score obtained in each question was then added to reach a final score. For the critical appraisal tool for cross-sectional studies, low quality refers to studies scoring 0 to 8, medium quality to studies scoring 9 to 12 and high quality to studies scoring higher than 12. For the critical appraisal tool for prevalence studies, low quality corresponded to a 0 to 9 score, medium quality to a 10 to 14 score and high quality to a score of 15 or higher.This study had the publication bias of not analyzing the gray literature, in addition to not including studies that were not published because they did not present data considered relevant for publication.Meta-analysis was performed to assess the prevalence of TB (active and/or latent) in prisoners. The results are presented as prevalence, in percentage, through random effects models, with a confidence interval of 95%. The heterogeneity between the studies was evaluated using the I2 test, in which values above 50% and p-value less than 0.05 were considered as high heterogeneity .To be included in the meta-analysis, the study had to inform on the number of people with TB, active and/or latent, and the total sample size. If the study only provided data on the percentual prevalence, the number of people was calculated. Analysis was stratified according to the burden of TB in the country where the study was conducted (high burden country for TB/ not high burden country for TB). We used the list of countries of high TB burden of the Global Tuberculosis Report of 2020 . AnalysiSearches of the databases yield a total of 3122 articles  of which 1148 were duplicates and 283 were in other languages besides those defined for this SR. A further 1493 articles were excluded after applying eligibility criteria to title and abstract. A total of 268 publications were considered for full-text assessment, of which 30 were excluded because it was not possible to access them, 55 did not meet the eligibility criteria , 5 studied prisoners with co-infection TB-HIV, 3 compared strains of Koch bacilli, 3 concerned TB outbreaks, 2 studied homeless people, 2 were on-going clinical trials, 2 jointly addressed prison officials and prisoners, 3 were editorials, 3 were commentaries, 3 were on vulnerable populations as a whole, 2 were legislative reviews, 3 specific evaluations and tests on incarceration rate, increased risk of TB in the general population or juvenile prisoners) and 3 were duplicates not previously identified. A total of 180 articles met the inclusion for the initial scoping review and of these 74 studies presented prevalence results and were included in the meta-analysis reported in this paper , followed by Ethiopia (n = 9), USA (n = 5), Spain (n = 3) and Zambia (n = 3), Malaysia n = 2), Malawi (n = 2), Pakistan (n = 2), Bangladesh (n = 2), South Africa (n = 2) and India (n = 2), Turkey (n = 2), Colombia (= 2) . Prisons produce favourable conditions for the expansion of the TB epidemic in the general population. A study carried out in Brazil showed that incarcerated individuals enter prisons with a low risk of TB . HoweverWhen comparing studies conducted in low- and low-middle-income countries with those in high and high-middle income, it was also possible to observe higher prevalence in low- and low-middle-income countries of active and latent TB and among symptomatic prisoners . HoweverIn this analysis, only 22 studies were conducted in high burden TB countries who were middle/high income countries , with 19 of them being conducted in Brazil. The remaining studies were done in low- and lower-middle-income countries with high burden of disease. More than 90% of reported TB infections occur in low- and middle-income countries . Low-inccirca 2.1 times higher than medium and low-quality studies. In relation to latent tuberculosis, high-quality studies had higher rates than those of medium quality. In studies that included symptoms of TB, the rates were higher in the two medium and low quality ones, thus resulting in a frail evidence of this difference.High quality studies had active TB prevalence rates The global prevalence of latent TB in the general population according to the World Health Organization-WHO is a quarter of the world's population . A systeIn the general population, in 2018, about 10 million people were notified with TB worldwide, equivalent to 132 per 100,000 population a 2% decline from 2017. From 2000 to 2018 there was a 1.6% drop in the incidence of TB in the general population [110]. According to the WHO, over a 20-year period, the overall incidence of TB ranged from a maximum of 174 cases per 100,000 population in the year 2000 to a minimum of 127 cases per 100,000 population in the year 2020, these numbers are lower than those found in the prisoner population [111].Focusing interventions on prisons can have powerful effects in reducing TB rates in the general population as investing in tuberculosis control in 0.5% of the population would reduce the total incidence of active TB in the population by more than 40% .Prisons are potentially transmitting place for TB: not only due to its poor structure conditions but also because of the social issues that migrate from the outside world with the imprisonment of individuals.The metanalysis conducted suggests that TB, and probably other infectious diseases, find fertile ground in prisons where previous acquired social disadvantages seem to thrive.Therefore, TB in prisons should be understood as a global public health problem because TB is not only a health problem, but also a social problem, effective strategies to control the disease are needed targeting the prison environment, including rapid health assessments to understand each context and to implement tailored and precision interventions.Additional file 1. Search strategy.


There is no information on the commonality and specificity of oral and fecal microbiota in patients with gastric cancer (GC) and colorectal cancer (CRC).The high-throughput 16S rRNA gene V4 region sequencing was used to perform bioinformatics analysis of oral, fecal, and tissue microbiota in GC (76 subjects), CRC (53), and healthy controls . Furthermore, we determined the microbial characteristics of each part, constructed and verified three classifiers for GC and CRC, and evaluated curves of receiver operating characteristic and precision–recall with probability of disease.Haemophilus, Neisseria, Faecalibacterium, and Romboutsia were significantly reduced compared to the relative abundance value of oral or fecal bacterial genera in the HC group, while the Streptococcus, Gemella, Escherichia-Shigella, and Fusobacterium were significantly increased. The oral and tissue microbiota have similar and abundant shared bacterial networks. The single and combined microbial detection have good AUC values based on POD indices for predicting GC, CRC, and gastrointestinal (GI) cancers (GC and CRC).Compared to HC, the microbial richness and diversity of GC and CRC decreased in oral cavity and increased in stool; additionally, these indexes in GC tissue were higher than those in CRC tissue. In GC and CRC patients, Haemophilus, Neisseria, Faecalibacterium, Romboutsia, Streptococcus, Gemella, Escherichia-Shigella, and Fusobacterium) may be involved in tumor evolution as potentially characteristic genera. In addition, both oral and fecal microbial detection may provide a solid theoretical foundation for the non-invasive prediction of these cancers.This study is the first to examine the characteristics of oral, fecal, and tumor microbiota in GC and CRC patients, and the similarities and differences in their microbial changes are reported. These oral or fecal bacteria ( Helicobacter pylori infection contributes significantly to non-cardiac GC development  is the fifth most common cancer and the fourth leading cause of cancer death worldwide, with half of all cases occurring in East Asia (primarily in China) . Helicobelopment , and itselopment . Only 1%velop GC . Many stelopment . The endelopment . Althougelopment , magnetielopment , and serelopment , there iThe diversity and richness of microbiota change significantly during the evolution of superficial gastritis (SG), atrophic gastritis (AG), intestinal metaplasia (IM), and GC . With thCRC is now the third most common cancer and the second leading cause of cancer death worldwide with an increase in morbidity and mortality rates in China over the last decade . Colonos11 types of bacteria) each day, almost all of which enters the GI tract, forming a loop between the subject’s oral, fecal, and GI microbiota  were reported in this study. Furthermore, we evaluated the potential of oral and fecal microbiota as non-invasive biomarkers for GC and CRC through the validation cohort and diagnostic cohort.The body produces approximately 1,000 ml of saliva  adopting prospective specimen collection and retrospective blind evaluation (PRoBE) methods . Before Following isolation of lesions surgically, the samples comprising cancer lesions and paracancerous tissues  were transferred into a 3-ml RNAlater sterile cryotubes  and transported to the laboratory in an ice pack and stored it at −80°C until further use.The oral samples were collected by swabbing the medial sides of both cheeks of the subjects using a cotton swab , followeThe subject’s fresh stool samples were collected in a special stool tube sterilized internally and were packed using ice packs and delivered to the laboratory for further processing. The samples were divided into 200-mg portions and kept at −80°C until further use. The oral and fecal samples were collected prior to surgery in GC and CRC inpatients.® DNA PCR-Free Sample Preparation Kit  according to manufacturer’s instructions and index codes were added. The Qubit@ 2.0 Fluorometer (Thermo Scientific) and Bioanalyzer 2100 system (Agilent) were used to evaluate the library’s quality. The library was sequenced on an Illumina NovaSeq platform , resulting in 250-bp paired-end reads.Total genome DNA from samples was extracted using the CTAB method. DNA concentration and purity was monitored on 1% agarose gels. According to the concentration, DNA was diluted to 1 ng/µl using sterile water. The high-throughput 16S ribosomal RNA gene sequencing was carried out using specific primers of 16S rRNA gene V4 region 515F: -GTGCCAGCMGCCGCGGTAA- and 806R: -GGACTACHVGGGTWTCTAAT-. The sequencing libraries were created using a TruSeqPaired terminal readings were assigned to each sample based on its unique barcode and truncated by excising the barcode and primer sequences. FLASH was used to perform sequence assembly . The datSequence analysis was performed using Uparse software. Sequences with ≥97% similarity were assigned to the same OTU. The Silva database was used to annotate classification data using Mothur algorithm . MultiplThe raw data were normalized by the QIMME1/normalize module [cumulative-sum scaling (CSS)]. The α-diversity of each sample was evaluated by richness (Chao 1) and biodiversity (Shannon) . These iThe optimal OTU marker described above was determined using fivefold cross-validation. The POD index was defined as the ratio between the number of randomly generated decision trees with predicted samples such as GC, CRC, or GI to the number of healthy controls. The optimal OTU set was used to calculate POD indices for the training and testing cohorts. The receiver operating characteristic (ROC)  area under the curve (AUC) was used to represent the ROC effect. Characteristic biomarker genera were found by Random Forest  .H test, chi-square test, or Fisher’s exact test , GraphPad Prism V.9.0 , and Microsoft Excel  were used for statistical analysis. The statistical significance was set at p < 0.05.The clinical data were analyzed using one-way ANOVA, the Kruskal–Wallis act test Table 1.A total of 435 oral and fecal samples from the same area were prospectively collected. Of these, 334 samples  were included after systematic elimination and pathological diagnosis. Meanwhile, 117 tumors and paracancerous tissues were collected from some participants . The above samples were acquired from 199 qualified participants  and were randomly divided into a discovery phase and a verification phase. In the discovery phase, we characterized microbiota of 72/71 HC , 68 GC , and 37 CRC , and identified microbial markers. The GC and CRC classifiers were constructed by using the random forest model between the GC/CRC cohort and the HC cohort. In the validation phase, we used 68/69 HC , 61 GC , and 38 CRC  to validate diagnosis efficacy of the GC and CRC classifiers. Furthermore, all oral samples  and fecal samples  were used as another independent diagnostic stage to verify the potential of the GC and CRC classifiers Figure 1The analysis of clinical data revealed that, compared to GC and CRC, the number of people in HC who met these criteria  increased significantly. In dietary surveys, healthy people had a higher frequency of intake of fresh fruits and a lower frequency of intake of high-fat foods than GC and CRC groups Table 1.The rank abundance curve showed that, compared to oral and fecal samples, the microbiota in GC and CRC tissue had greater richness and evenness , while that of Haemophilus and Neisseria were less abundant (p < 0.05). In comparison to fecal flora of the HC group, Escherichia-Shigella and Streptococcus were more abundant (p < 0.05) in the stools of GC and CRC patients, while Faecalibacterium, Dialister, and Romboutsia were less abundant (p < 0.05). Meanwhile, Fusobacterium and Akkermansia were more abundant (p < 0.05) in the stool of CRC patients, and Megamonas was less abundant (p < 0.05). Interestingly, Fusobacterium was less abundant (p < 0.05) in the CRC oral cavity samples compared to the HC oral group. The different bacteria  in GC and CRC tissues were also evaluated and they differed in oral, fecal, and tissue flora  and MetaStat analysis, we further analyzed the relative abundance values of the different bacterial genera (LDA > 4) among the groups. In comparison to oral flora of the HC group, Fusobacterium) were pathogenic and were linked to the late colonization of oral biofilms and several human diseases (including CRC and juvenile periodontitis). Actinomyces, Haemophilus, Rothia, Streptococcus, and other genera existed in the early stage of dental biofilm formation and were associated with relatively healthy dental pockets, which were defined as Biofilm CAG (Actinobacteriota (OTU_9 and OTU_50) and Biofilm CAG  of GC oral samples vanished completely. The bacterial network in CRC tissue was sparser (number of OTUs and lines) compared to that in GC tissue. Similar bacterial networks in tumor and paracancerous tissue may indicate that the bacterial composition of diseased organs has changed before tumor formation , as community structure may provide more valuable information than differences in the abundance of individual genera. To investigate the microbiota correlation between HC, GC, and CRC in oral, fecal and tissue samples, 16 OTUs shared between oral and tissue samples of participants from the three groups were screened. These 16 OTUs were expressed in at least 30% of all oral and tissue samples from the three groups and had more than 300 reads in a single sample. In addition, 16 OTUs were shared between fecal and tissue samples from the three groups of participants, which were expressed in at least 30% of all fecal and tissue samples across all three groups, with >300 reads in a single sample Table S6film CAG . The oraA random forest classifier model to determine the diagnostic value of oral and fecal microbiota for GC, CRC, and GI cancers were generated. A 5-fold cross-validation was used to achieve specific cancer identification Table S7Proteobacteria and CRC Fusobacteriota content decreased in oral samples (LDA > 4), while they increased in fecal samples (LDA > 4). At the genus level, compared to HC, the content of Haemophilus and Neisseria of GC and CRC decreased, while the content of Streptococcus and Herbaspirillum increased in oral samples (LDA > 4); in addition, the content of GC’s Streptococcus and Escherichia-Shigella and CRC’s Fusobacterium and Escherichia-Shigella increased in stool samples (LDA > 4). Through the comparison of the three algorithms of Lefse, RF, and PLSDA-VIP, these shared differential genera  were found, and may play a role in GC/CRC. We also further compared the relative abundance of different bacterial genera (LDA > 4)  in the oral cavity, stool, and tissue among multiple groups. The results suggested that they could be used as potential biomarkers to participate in the evolution of tumors as passengers or drivers. However, the significance of the synergistic or antagonistic relationship between microbiota must be investigated further. These oral and fecal bacterial changes appear to be regular, and further research into their interactions may provide new insights into tumorigenesis. Furthermore, significant differences from HC bacteria served as a foundation for GC and CRC-specific prediction.In this study, a combined analysis of GC and CRC was performed, demonstrating the commonality and specificity of microbiota in the oral cavity, stool, tumor, and paracancerous tissue. Compared to HC, GC and CRC showed the same changes in the richness, evenness, and number of bacterial species, revealing that the indicators decreased in oral samples and increased in fecal samples. Similar changes were observed in the α-diversity. Microbial dysbiosis may be caused by a decrease in low-abundance bacteria and a change in their composition in GC and CRC oral samples and an increase in microbial diversity in fecal and tumor samples. Meanwhile, compared to HC, the GC H. pylori, which accounts for 72%–99% of sequencing reads (Helicobacter genus in tumor (<25%) and paracancerous tissue (<50%) implies that other bacteria may play more important biological functions in GC. Although the acidic environment of a healthy stomach is not conducive to bacterial growth, the bacterial richness and several GC α indexes were higher in the tissue samples than those of CRC, indicating a change in GC tissue environment and rich microbial diversity. Streptococcus was found to be more abundant in GC tumors than in paracancerous tissue, and Fusobacteriota and Fusobacterium were found to be more prevalent in CRC tissue   could help reduce the burden of GC and CRC . Microbiia coli) . Variousia coli) .https://www.ncbi.nlm.nih.gov/sra/PRJNA778008.The original contributions presented in the study are publicly available. These data can be found here: This study was approved by the Committee on Medical Ethics of the First Affiliated Hospital of Anhui Medical University (Quick-PJ 2021-13-23). The patients/participants provided their written informed consent to participate in this study.Study concept and design: CZ and YoL. Specimen provider: CZ, AH, and YaL. Analysis and interpretation of data: CZ, AH, and JL. Technical and material support: YoL, CZ, and PZ. Drafting of the manuscript: CZ. All authors contributed to the article and approved the submitted version.This work was supported by grants from the National Natural Science Foundation of China (No. 81874063) and the Natural Science Foundation of Anhui Province (No. 2008085QH408).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


P < 0.001; I2 = 98%). We conducted subgroup analyses of Chinese  and non-Chinese studies . The sensitivity analysis by risk of bias continued to demonstrate an association, and the heterogeneity remained unchanged . Higher AIP values were associated with higher odds of developing CAD.Various studies suggest that the atherogenic index of plasma (AIP) is associated with the risk of coronary artery disease (CAD) in different clinical scenarios. This review aimed to synthesize evidence of the association between AIP values and CAD. A literature search was carried out on four databases, namely, PubMed, Scopus, Web of Science, and Ovid-Medline. A handsearch was performed on preprint repositories (MedRxiv and Research Square). The effect measurements were expressed as odds ratios (OR) with their corresponding 95% confidence intervals (CI). For the quantitative synthesis, we employed a random-effects model. We analyzed 14 articles  from seven different countries. The quantitative analysis revealed that an increase in one unit of AIP was associated with higher odds of developing CAD (OR 2.11; 95% CI 1.65–2.69;  In Cardiac risk stratification is necessary to improve preventive and therapeutic interventions . BiomarkHypertriglyceridemia and low HDL levels are independent markers of CHD ,16. TherThus, several studies have suggested that AIP acts as a marker associated with cardiovascular diseases in patients with various pathologies ,20,21,2222.1We conducted this systematic review in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement . The sum2.2We conducted a literature search on articles that evaluated the association between AIP and CAD on October 15, 2021. Four databases were searched: PubMed, Scopus, Web of Science, and Ovid-Medline. A handsearch was also performed on preprint repositories (MedRxiv and Research Square) (see Supplementary Appendix 1).2.3The articles collected from the aforementioned databases were exported to the Rayyan data management software , and dupOnce this phase was completed, each of the articles was read in full-text, and we determined whether they met the previously established selection criteria. A study was excluded if it failed to comply with the selection criteria. If an article did not contain the required information, an attempt was made to contact the corresponding author of the said article. A secondary bibliographic search was conducted on the articles that reached the full-text review phase.In case of disagreements on the inclusion or exclusion of an article, a third reviewer was consulted. Finally, information of the selected articles was extracted and collated in a standardized Excel 2016 document. The extracted data included author name, country, year of publication, study sample, study design, population characteristics , exposure (AIP mean or median of the whole sample and according to sample stratification), and crude/adjusted association measures . Outcome definitions are presented in Table S2.2.4P-values > 0.1 were considered indicative of no publication bias.Four authors  evaluated the included studies independently using the Newcastle–Ottawa Scale . The stu2.5I2-statistic, where values >60% were considered to indicate severe heterogeneity. A Cochran’s Q test was also conducted, where a P-value < 0.05 was considered statistically significant. A random-effects model was used for the meta-analysis as we anticipated heterogeneity among studies. In the subgroup analysis, we conducted a comparison between associations according to country (Chinese vs non-Chinese studies), study design, CAD definition, and gender (women vs mixed). In the sensitivity analysis, we excluded studies with a high risk of bias. We also analyzed all studies after transforming OR to RR. In addition, we performed a meta-regression, reported as bubble plots, in order to search for heterogeneity sources, due to differences in the clinical and methodological characteristics of the individual studies. Assessed variables were study design, study location, CAD definition, and gender.The quantitative analysis was conducted using the RevMan 5.4 statistical program . The OR and their corresponding 95% confidence intervals (CI) were the only effect measures used; thus, we transformed standardized mean differences to ln[OR] using the Chinn method. RR was converted into OR ,26. Vari33.1The search strategy yielded 975 records. After removing 610 duplicates, 365 articles finally remained. After evaluating the titles and abstracts, we excluded 322 more studies. Then, a full-text review was performed on the remaining 43 articles, which led to the exclusion of 29 more articles. In the end, 14 articles were included in the qualitative analysis and meta-analysis ,38,39,403.2The characteristics of each study are presented in detail in 3.3Table S3 presents the results of the methodological quality assessment. In summary, 10 and 4 studies were classified as having a low and moderate risk of bias, respectively.3.4P < 0.001) (I2 = 98%). Statistically significant associations with high heterogeneity were observed in all subgroup analyses by study location , whereas in the other, all OR values were transformed to RR ; however, the association with high heterogeneity remained in both cases   with sevlocation , study dlocation , definitlocation , and genlocation . Sensitilocation  were incth cases .3.5P = 0.974) , study design (P = 0.959) , CAD definition (P = 0.614) , or gender (P = 0.958) .No significantly associated coefficient was observed in study location (3.6P = 0.956), and the funnel plots did not show asymmetry .There was no indication of small-study effects , whose expression in AIP reflects the complex interactions of lipoprotein metabolism and is useful in predicting plasma atherogenicity . sdLDL hFor the aforementioned reasons, our finding of an association between high AIP values and increased CAD risk is not surprising. In addition to the aforementioned factors, factors associated with specific CAD conditions could also explain our results. In this context, some studies have found an association between AIP and arterial stiffness in normotensive patients , which iContrarily, in a multinational study in seven countries from 2003 to 2015, this association was independent of traditional risk factors . SimilarFinally, some studies demonstrated an association between AIP and the evolution of patients with acute coronary syndromes and myocardial infarction. For example, a Turkish study found that AIP was independently associated with the absence of reflow in patients with ST-elevated myocardial infarction following the primary percutaneous coronary intervention . SurprisThe meta-analysis conducted by Wu et al.  found thDespite the evidence suggesting an association between AIP and CAD, this is a systematic review and meta-analysis that systematize the available evidence. We also conducted sensitivity analyses considering the biases of the studies and the place of origin of the studies, which provided robustness to our results. The findings obtained allow us to suggest the use of AIP as a potential low-cost marker of CAD that will allow health personnel to prioritize management strategies and could even be used as part of predictive scores, replacing markers such as triglycerides. Similarly, the usefulness of this marker is independent of the age of the patients ,62, althOur systematic review has some limitations that must be acknowledged. First, there is evidence of high statistical heterogeneity due to the clinical and methodological differences between the analyzed studies. Second, most studies have not controlled the AIP values for confounding variables that impact the proposed outcome. Sociodemographic lifestyles and comorbidity variables should be considered in future studies to avoid confounding bias. Despite this, the direction of the effect is consistent in most of the reported studies. Third, most studies were conducted in Asia, with few or no studies found in other continents. Therefore, it is important to analyze the AIP value in CAD risk in these populations to establish its usefulness. Fourth, no definitive cutoff points have been reported to set the sensitivity and specificity of the AIP in CAD; thus, it is necessary to address it in future research in various contexts and populations. Finally, our findings indicate that high AIP values are associated with a greater possibility of suffering from CAD; however, with the obtained evidence, we consider that AIP is a risk marker and not a causal risk factor because the causes of lipid alterations are mediated by genetic and environmental factors. The AIP in altered ranges would be the expression of this multicausality and, therefore, a biomarker of the pathophysiological process leading to the appearance of CAD.5This systematic review and meta-analysis demonstrated that patients with higher AIP values have higher odds of developing CAD. However, additional primary studies are warranted to define an optimal cutoff point of AIP to predict CAD.