Potential Variables Research Articles

Psychosocial and sociodemographic factors associated with gestational blood glucose levels in women attending public hospitals: Results from baseline of MAASTHI cohort.

Understanding psychosocial environment is important for improving maternal and fetal health outcomes during pregnancy. We aimed to identify the association between gestational blood glucose levels and psychosocial and demographic factors in pregnant women. In the MAASTHI pregnancy cohort in Bengaluru, we assessed depressive symptoms, and social support using validated scales at baseline in first trimester. A 2-hour 75 g oral glucose tolerance test (OGTT) was administered between 24-36 weeks of gestation. We examined the relation between psychosocial factors assessed at baseline and gestational blood glucose levels in second/third trimester using multivariate linear regression and explored association between serum cortisol and gestational blood glucose levels in subgroup samples. We found that 9% of pregnant women had depressive symptoms and 14.3% had Gestational Diabetes Mellitus (GDM). Psychosocial factors, including depressive symptoms, have a significant correlation with gestational fasting(β = 0.12, p-value<0.05) and postprandial blood sugar level(β = 0.23, p-value<0.05) and poor social support were found to have a significant association with gestational fasting blood glucose levels(β = 1.45, p-value <0.05) and postprandial blood sugar levels(β = 2.60, p-value <0.05). The sociodemographic factors such as respondent education, occupation, social and economic status were associated with gestational blood sugar after adjusting for potential confounder variables. Depressive symptoms and poor social support earlier in pregnancy were significantly associated with increased gestational blood glucose levels. Early detection and recognition of modifiable psychosocial risk factors can reduce glucose intolerance during pregnancy. Evaluating the benefits of screening for psychosocial factors and timely management of gestational diabetes mellitus can be helpful in India.

Mapping variability of soybean leaf potassium concentrations to develop a sampling protocol

AbstractThe spatial variability of soybean [Glycine max (L.) Merr.] leaf‐K (potassium) concentrations must be considered when collecting samples to monitor crop K status. Five commercial soybean fields were sampled at a 0.4‐ha grid resolution at two reproductive growth stages to quantify the trifoliolate tissue‐K concentration. The objectives of this study were to identify the potential field variability of soybean leaf‐K concentrations in typical Mid‐south US soybean production fields, evaluate interpolation methods, and develop a sampling protocol for in‐season soybean tissue monitoring. No consistent spatial dependencies were found in the leaf‐K concentrations across the fields and sample times, indicating that a soybean tissue‐K grid sampling protocol cannot be generalized to a specific area size. Inverse distance weighted (IDW) and rasterization interpolation methods were considered to predict leaf‐K concentrations between the sampled grid points at grid resolutions ranging from 0.4 to 4 ha. The IDW method consistently predicted leaf‐K concentrations between the known values with less error than rasterization. Rather than grid sampling, composite leaf samples should be collected based on management zones to provide a simplified sampling protocol. Within each management zone, a composite sample must consist of uppermost fully expanded trifoliolate leaves collected from at least 18 locations to ensure that the sample measures within the 95% confidence interval of the area average leaf‐K concentration. The developed sampling protocol coupled with the dynamic critical tissue‐K concentration curve will provide producers with the ability to effectively monitor soybean for potential hidden hunger and verify K deficiency symptoms in season.

The first molecular characterization and phylogenetic analysis of bovine papular stomatitis virus in Iran

Bovine papular stomatitis (BPS) generally is a mild viral disease caused by the Bovine papular stomatitis virus (BPSV) belonging to the genus Parapoxvirus (PPV). This study aimed to perform the first molecular characterization and phylogenetic analysis of BPSV in beef calves in Iran. Clinical examinations were carried out on four beef cattle herds in West Azerbaijan province, which had experienced outbreaks of papular lesions. Fifty swab samples were collected from the papular lesions on the muzzle, lips, and oral cavity of affected calves, and after viral DNA extraction, they were subjected to polymerase chain reaction (PCR). The results of PCR confirmed the presence of BPSV in all calves with clinical symptoms. The partial B2L gene was sequenced based on nucleotides, and phylogenetic analysis was performed using MEGA 11.0.13. The analysis revealed that BPSV isolates from beef calves in Iran formed two clades. Clade 1 exhibited similarities to the isolates from Finland, Japan, and Georgia, while Clade 2 was similar to the Zambian isolates. These findings indicate the presence of genetic diversity and potential variability within the virus population. Further studies with larger sample sizes and diverse geographic regions will increase the resolution of the phylogenetic tree and contribute to a comprehensive understanding of how BPSV circulates in the country.

Social and biological factors associated with unsuccessful TB treatment outcome in Ireland 2011-2021

Abstract Background Tuberculosis (TB) treatment success rates are crucial for TB control programme evaluations. The World Health Organisation sets targets of &amp;gt; 90% but Ireland remains below 70%. We analysed notifications from the Irish National TB Surveillance System from 2011-2021 to explore factors associated with successful treatment outcome in Ireland. Methods We selected potential predictor variables based on clinical relevance and literature review. We examined each predictor's unadjusted association with treatment success using univariable logistic regression. We used backwards elimination to remove predictors that failed to remain significant in multivariable logistic regression. Treatment success was defined as treatment completed or cured, while unsuccessful treatment was defined as treatment failed, treatment interrupted, transferred out and died from any cause. We used Stata for analysis. Results Between 2011-2021, 52% of cases were successfully treated, 10.7% were unsuccessfully treated and treatment outcome was not reported for 37%. Treatment outcome completeness declined significantly between 2019-2021. Univariable analysis showed successfully treated cases had higher odds of being a migrant (OR:1.9; 1.5-2.5), being linked to outbreaks (OR:1.9; 1.2-3.0), being a contact of a case (OR: 1.0-2.5;), having a normal X-ray (OR:1.7;1.1-2.6) and being an outpatient (OR:3.0;2.2-4.2). Significant predictors of unsuccessful treatment in the final model were age &amp;gt;70 years, unemployment, immunesuppression and any anti-TB drug resistance. Conclusions Surveillance data shows that Ireland fails to meet the WHO target of &amp;gt; 90% treatment success with high levels of missing data. Data quality improvement initiatives are needed to reverse the decline in completeness associated with the Covid-19 pandemic period so control programmes can robustly evaluate performance. Additional supports should be considered for patients who are older, unemployed, immunesuppressed or with drug resistant TB. Key messages • Additional patient supports should be considered for patients who are unemployed, age 70 years and older, immunesuppressed or with drug resistant forms of TB. • Ireland fails to meet the WHO TB treatment success target with high levels of missing data. Treatment outcome completeness needs to be improved so control programmes can robustly evaluate performance.

Information technology capability, open technological innovation and firm growth.

The aim of this paper is to investigate the effects of information technology (IT) capability on firm growth in the context of open technological innovation. The paper utilized a logical deductive approach to develop hypotheses and analytical frameworks, and collected empirical data from 256 Chinese new ventures. Regression analysis and structural equation models were used to test the hypotheses and analyze the data. The results showed that IT capability, including flexibility and integration of information technology, significantly influenced firm growth, and open technological innovation partially mediated the relationship between IT flexibility and firm growth, and significantly mediated the relationship between IT integration and firm growth. The paper's limitations include the cross-sectional design, limited sample size, and potential unobserved variables such as organizational learning that could affect the relationship between IT capability and firm growth. The research is the first to investigate the effects of IT capability on firm growth based on the mediation of open technological innovation in China, contributing to the literature on IT capability and providing insights for managerial practice in the sharing economy era.

Changes in the epidemiological pattern of chronic B hepatitis amongst inmates in Catalonia: current prevalence and predictive variables.

The epidemiology of chronic hepatitis B (CHB) in Spain has changed due to migratory movements and the implementation of vaccination programs. The objective is to determine if prevalence has also changed amongst in Catalonia and the potential predictive variables of the infection. Observational cross-sectional multi-centre study of CHB prevalence. Epidemiological and clinical variables were included, and their predictive capacity is analysed by means of a multivariable logistic regression model. A total of 6508 prisoners were studied. CHB prevalence was 1.7%, much less than in studies carried out in previous years. In inmates from North Africa, Asia, Eastern Europe, and Sub-Saharan Africa the CHB rate was 2.8, 4.2, 4.9 and 16.2 times higher, respectively, than amongst those born in Spain, which was 0.6%, the same as in the general population. CHB was associated with: a) being an immigrant [2.6%; OR: 4.18 (CI: 2.50-6.90; P <0.001); b) being unvaccinated (3.1%; OR: 0.13; CI: 0.06-0.26; P <0.001); and c) being infected by the human immunodeficiency virus (HIV) [3.9%; OR: 3.23; CI: 1.24-8.40; P = 0.016]. Vaccination against HBV (hepatitis B virus) has greatly reduced CHB prevalence in inmates over the past 30 years but remains high in immigrants and those with HIV. We recommend: a) maintaining HBV screening amongst inmates; b) continuing with vaccination programmes; and c) referring CHB cases to specialized programs for further study and treatment if needed.

Machine learning model for predicting physical activity related bleeding risk in Chinese boys with haemophilia A

BackgroundPhysical activity is a crucial part of an active lifestyle for haemophiliac children. However, the fear of bleeds has been identified as barriers to participating physical activity for haemophiliac children even with prophylaxis. Lack of evidence and metrics driven by data is key problem. ObjectivesWe aim to develop machine learning models based on clinical data with multiple potential factors considered to predict risk of physical activity bleeding for haemophilia children with prophylaxis. MethodsFrom this cohort study, we collected information on 98 haemophiliac children with adequate prophylaxis (trough FVIII:C level > 1 %). The involved potential predictor variables include demographic information, treatment information, physical activity, joint evaluation, and pharmacokinetic parameters, etc. We applied CoxPH, Random Survival Forests (RSF) and DeepSurv to construct prediction models for the risk of bleeding during physical activities. All three survival analysis models were internally and externally validated. ResultsA total of 98 patients were enrolled in this study. Their median age was 7.9 (5.5, 10.2) years. The CoxPH, RSF and DeepSurv models' discriminative and calibration abilities were all high, and the RSF model had the best performance (Internal validation: C-index, 0.7648 ± 0.0139; Brier Score, 0.1098 ± 0.0015; External validation: C-index, 0.7260 ± 0.0154; Brier Score, 0.0930 ± 0.0018). The prediction curves demonstrated that the developed RSF model can distinguish the risks well between bleeding and non-bleeding patients, as well as patients with different levels of physical activity. Meanwhile, the feature importance analysis confirmed that physical activity bleeding was deduced by comprehensive effects of various factors, and the importance of different factors on bleeding outcome is discrepant. ConclusionsThis study revealed from the mechanism that it is necessary to incorporate multiple factors to accurately predict physical activity related bleeding risk. In clinical practice, the designed machine learning models can provide guidance for children with haemophilia A to positively participate in physical activity.

Perceptions and predictors of health-related quality of life among aging adults who stutter: a first glimpse

ABSTRACT Quality of life among adults who stutter (AWS) is well-studied but little is known about health-related quality of life, an index of successful aging. The study’s aim was to begin documenting perceptions and predictors of physical and mental health quality of life (PH-, MH-QoL) among aging AWS. Forty AWS (50-84 years old) in the United States completed the SF-36 survey of PH- and MH-QoL, and were surveyed on potential explanatory variables including resilience, social resources, health-promoting behavior, socioeconomic status, perceptions of aging, social risk, identity management, neuroticism, stuttering severity, and difficulty communicating. The prevalence of very low PH- and MH-QoL scores was compared against age- and gender-graded population norms. Finally, PH- and MH-QoL scores were regressed onto explanatory variables. Relatively few aging AWS had very low PH-QoL scores. A non-trivial subset of aging AWS had very low MH-QoL scores. Greater awareness of aging-related loss predicted lower PH- and MH-QoL. Greater neuroticism also predicted lower MH-QoL. Greater resilience predicted better MH-QoL. If replicable, results would suggest few aging AWS are at-risk for very low PH-QoL while more aging AWS are at-risk for very low MH-QoL. Predictors of PH- and MH-QoL may inform strategies for successful aging among AWS.

Cognitive reappraisal in mHealth interventions to foster mental health in adults: a systematic review and meta-analysis

BackgroundAn increasing number of mHealth interventions aim to contribute to mental healthcare of which interventions that foster cognitive reappraisal may be particularly effective.ObjectivesTo evaluate the efficacy of mHealth interventions enhancing cognitive reappraisal to improve mental health in adult populations.MethodsThe literature search (four databases) yielded 30 eligible randomized controlled trials (comprising 3,904 participants). We performed a multi-level meta-analysis to examine differences between intervention and comparator conditions at post-intervention assessment. Moderator analyses were conducted for potential moderator variables (e.g., type of comparators).ResultsMost interventions were CBT-based with other training components in addition to cognitive reappraisal. We found preliminary evidence for a small to medium effect favouring mHealth interventions to enhance cognitive reappraisal over comparators, M(SMD) = 0.34, p = .002. When analysing single symptoms, there was evidence for a small to medium effect of mHealth interventions on anxiety and depressive symptoms, but not for psychological distress and well-being. All analyses showed substantial heterogeneity. Moderator analyses revealed evidence for more favourable effects in studies with passive comparators. There was an overall high risk of bias in most of the studies.ConclusionsWe found preliminary evidence for a small to medium effect of mHealth interventions including a cognitive reappraisal component to improve mental health. However, most of the interventions were complex (i.e., reappraisal was provided alongside other components), which prevents us from examining reappraisal-specific effects beyond general mental health promotion in mHealth. Dismantling studies examining the effects of single intervention components are warranted to corroborate these promising results.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=142149, identifier [CRD42019142149].

Predictors of successful endovascular recanalization in patients with symptomatic nonacute intracranial large artery occlusion

BackgroundEndovascular recanalization in patients with symptomatic nonacute intracranial large artery occlusion (ILAO) has been reported to be feasible, but technically challenging. This study aimed to determine the predictors of successful endovascular recanalization in patients with symptomatic nonacute ILAO.MethodsThe outcomes of endovascular recanalization attempts performed in 70 consecutive patients showing symptomatic nonacute ILAO with hemodynamic cerebral ischemia between January 2016 to December 2022 were reviewed. Potential variables, including clinical and radiological characteristics related to technical success, were collected. Univariate analysis and multivariate logistic regression were performed to identify predictors of successful recanalization for nonacute ILAO.ResultsTechnically successful recanalization was achieved in 57 patients (81.4%). The periprocedural complication rate was 21.4% (15 of 70), and the overall 30-day morbidity and mortality rates were 7.1% (5 of 70) and 2.9% (2 of 70), respectively. Univariate analysis showed that successful recanalization was associated with occlusion duration, stump morphology, occlusion length, slow distal antegrade flow sign, and the presence of bridging collateral vessels. Multivariate analysis showed that occlusion duration ≤ 3 months (odds ratio [OR]: 22.529; 95% confidence interval [CI]: 1.636-310.141), tapered stump (OR: 7.498; 95% CI: 1.533–36.671), and occlusion length < 10 mm (OR: 7.049; 95% CI: 1.402–35.441) were independent predictive factors for technical success of recanalization.ConclusionsOcclusion duration ≤ 3 months, tapered stump, and occlusion length < 10 mm were independent positive predictors of technical success of endovascular recanalization for symptomatic nonacute ILAO. These findings may help predict the likelihood of successful recanalization in patients with symptomatic nonacute ILAO and also provide a reference for the selection of appropriate patients. Further prospective and multicenter studies are required to validate our findings.

Risk Approach Based on the FRAM Model for Vessel Traffic Management

Abstract This study analyzes the risks in ship traffic services management using the functional resonance analysis method (FRAM), a novel approach that focuses on identifying interactions leading to performance variability rather than errors. The research area is the Turkish Straits vessel traffic service management (VTSM) region, known for frequent risky ship passages. The goal is to ensure safe VTSM, minimize the negative impacts on people, goods, and the environment. The daily routine functions of the VTSM, determined through consultations with vessel traffic operators (VTOs), are explained by following FRAM analysis principles. Qualitative methods, aligned with expert opinions, are used to examine potential performance variabilities and hazard factors. The resulting risk situation for each function is categorized by criticality on a color-coded scale. Solution proposals are provided to manage critical function variability, enhancing the VTSM system's responsiveness and adaptability.

Development of a Low-Cost Artificial Vision System as an Alternative for the Automatic Classification of Persian Lemon: Prototype Test Simulation.

In the present research work, an algorithm of artificial neural network (ANN) has been developed based on the processing of digital images of Persian lemons with the aim of optimizing the quality control of the product. For this purpose, the physical properties (weight, thickness of the peel, diameter, length, and color) of 90 lemons selected from the company Esperanza de San José Ornelas SPR de RL (Jalisco, Mexico) were studied, which were divided into three groups (Category "extra", Category I, and Category II) according to their characteristics. The parameters of weight (26.50 ± 3.00 g), diameter/length (0.92 ± 0.08) and thickness of the peel (1.50 ± 0.29 mm) did not present significant differences between groups. On the other hand, the color (determined by the RGB and HSV models) presents statistically significant changes between groups. Due to the above, the proposed ANN correctly classifies 96.60% of the data obtained for each of the groups studied. Once the ANN was trained, its application was tested in an automatic classification process. For this purpose, a prototype based on the operation of a stepper motor was simulated using Simulink from Matlab, which is connected to three ideal switches powered by three variable pulse generators that receive the information from an ANN and provide the corresponding signal for the motor to turn to a specific position. Manual classification is a process that requires expert personnel and is prone to human error. The scientific development presented shows an alternative for the automation of the process using low-cost computational tools as a potential alternative.

Study on the effect of the molding process on the uniformity of rubber products

AbstractThe uniformity of rubber products stands as a pivotal indicator for assessing their overall quality. In the case of certain specialized rubber items, such as rubber bladders, uniformity emerges as a decisive criterion that significantly influences their quality evaluation. Numerous factors exert an impact on the homogeneity of rubber products. However, the comprehensive investigation of how the molding process influences such homogeneity remains notably underexplored. To mitigate the potential variability in experimental outcomes, this paper employs distinct pre‐treatment procedures for two types of rubber—designating one for the experimental group and the other for the control group. Subsequently, the items underwent distinct molding procedures to analyze the combined impact of pre‐treatment and molding techniques on the uniformity of rubber products. The findings indicate a notable enhancement in the uniformity of cylindrical rubber products—like rubber bladders—of up to 30% through the implementation of the filtration pre‐treatment process. Additionally, rubber products derived from the injection molding process demonstrated a remarkable 40% increase in uniformity compared to those produced through molding techniques.

Modeling the effect of slope aspect on temporal variation of soil water content and matric potential using different approaches by HYDRUS-1D

Slope aspect affects microclimate and soil moisture conditions, and thus has an important effect on the hydrological cycle. Given the lack of precise field data on this effect, two soil temperature, moisture and matric potential monitoring sites on north- and south-facing slopes have been established since 2017 in sandy loam soil under beech forest in a small valley near Ebergötzen, central Germany. HYDRUS-1D software was used with different approaches (including Rosetta, RETC, and RETC–measured θs approaches) for deriving soil hydraulic parameters of the van Genuchten model, to simulate temporal variability of soil water content and matric potential in the two slope aspects. Due to different microclimatic conditions, the south-facing slope was warmer and drier than the north-facing slope (two-years average temperatures 9.71 and 9.36 °C, and two-years average soil water contents 0.17 and 0.26 cm3 cm-3, respectively). The model was satisfactorily calibrated and validated on the two slopes. The calibration for the wet period was better on the south-facing slope (R2 = 0.772) than on the north-facing slope (R2 = 0.690). The simulation performance by HYDRUS-1D was better in the wet period than in the dry period. In the dry period, the model was better calibrated for the north-facing slope (R2 = 0.880) than for the south-facing slope (R2 = 0.691). The better calibration results for the wet period of south-facing slope can be explained by the location of the majority of measured soil water retention data which were in the near-saturation zone on the north-facing slope, and discontinuity of second-order derivative of the van Genuchten equation at saturation point when shape parameter (n) is smaller than 2. According to the model ability and different datasets used for the model validation, the north-facing plot was validated better than the south-facing plot for both wet and dry periods. Given that Rosetta was developed based on a soil hydraulic dataset from temperate climates, and the shortcomings of the hydraulic model, our results indicated that the Rosetta–derived approach was a reliable source for soil hydraulic parameters in both slope aspects for the wet period. However, the RETC–derived parameters were more accurate than Rosetta for the dry period on the north-facing slope.

Method of justification of the requirements for metrological support of repair of objects with variable structure

A new method of justification of the requirements for measuring equipment (ME) is proposed. For the first time, the method accounts for the potential variability of the product structure during its intended use, and thus, allows minimizing the requirements concerning the probability of estimating the values of diagnostic parameters of the product during its current repair (CR), thereby reducing the cost of ME. In addition, partial (in particular, time between failures and average recovery time) and multi-component (in particular, the readiness/non-readiness factors) values of the reliability indices are quantitatively estimated and which meet the requirements. The task is solved algorithmically using the approaches of technical diagnostics and metrology. Based on the prescribed requirements for the reliability indices of the product, the justified ME for CR is selected. To achieve the goal, recent advances in modelling the reliability of large-scale facilities and systems with variable structure, as well as metrology methods for assessing the impact of the reliability of the ME on the value of the average recovery time of multimode facilities during their CR are involved. To our best knowledge, the application of these possibilities has not been reported yet. The paper formalizes the procedure for applying the obtained results in the form of an algorithm, which allows increasing the efficiency of the method, benefiting from its advantages. The application of the proposed method is illustrated for a piece of real communication equipment, namely a subsystem controlling the functioning of a high-power radio transmitter. It is demonstrated that, based on the requirements stated in the guidance documents regarding the value of the average recovery time of an object with variable structure, the selection of metrological characteristics and type of ME can be justified. Alternatively, the problem can be solved based on the given value of the reliability index of a multicomponent product, the so-called readiness factor. An example of assessing the efficiency by the proposed method is presented. The proposed method is recommended for the development of metrological support for CR of prospective radio-electronic tools with variable structure.

Associations among post-partum rumen fill and motility, subclinical ketosis and fertility in Holstein dairy cows

This prospective observational study aimed to investigate the association of rumen fill and motility in post-partum Holstein cows with their future reproductive performance and subclinical ketosis (SCK). The study population consisted of two independent data sets: the first (DS1) included 237 cows from 6 herds and the second one (DS2) 709 cows from 9 herds. Rumen Fill Score (RFS) was transformed into a 3 level-trait, representing very low, low and adequate dry matter intake, respectively. A binary Rumen Contraction Score (RCS) was defined as: 0: <2 contractions/2 min, impaired rumen motility and 1: ≥2 contractions/2 min, normal rumen motility. A combined binary trait based on RFS and RCS (RFCS) was also established, representing unsatisfactory and satisfactory rumen function. Three SCK traits were defined, based on 3 different thresholds, SCK_I: BHB≥1,000 mmol/L, SCK_II: BHB≥1,100 mmol/L and SCK_III: BHB≥1,200 mmol/L. Scores were assessed and blood samples collected on day 7 (DS1) or day 8 (DS2), postpartum. Kaplan-Meier survival analysis, multivariable Cox proportional hazards models and Generalized Linear Mixed Models were performed to evaluate the association of rumen and SCK traits with reproduction. Herd, parity, calving season and several postparturient diseases were also included as potential explanatory variables. Mean days from calving to pregnancy after the 1st artificial insemination (AI) and from calving to pregnancy (all AIs) were shorter for levels of rumen traits representing adequate DMI and normal rumen motility; in most cases these differences were statistically significant in both datasets. Cows with adequate DMI and normal rumen motility (only in DS2) had greater hazard (hazard ratio [HR] = 1.84 and 1.61, for RFS and RFCS, respectively) and odds (odds ratio [OR] = 2.49 and 1.98, for RFS and RFCS, respectively) for pregnancy at 1st AI. Assessment of the association of examined rumen traits with hazard and odds for pregnancy at all AIs yielded statistically significant results in both datasets. For RFS, RCS and RFCS, HRs ranged from 1.57 to 3.31 and ORs from 1.95 to 4.83. No statistically significant associations with hazard and odds for pregnancy at 1st or all AIs were detected, for any of the 3 SCK traits, in either dataset. Overall, the combined RFCS trait constantly identified more than twice the number of cows with future reproductive problems than a positive SCK blood test.

Study the effect of the different doses from the laser on Staphylococcus aureus Bacteria growth in vitro

Background: Laser is a novel physical therapy technique used to treat various conditions, including wound healing, inhibition of bacterial growth, and postoperative wounds. High-power pulsed alexandrite laser therapy is one of the most prevalent forms of laser therapy, which is a noninvasive method for treating various pathological conditions, thereby enhancing functional capacities and quality of life. It is a modern medical and physiotherapeutic technology. Generally, the Alexandrite laser emits infrared light with a wavelength of 755 nm, allowing it to propagate and penetrate tissues. Objective: This study focused on the application of a high-power pulsed alexandrite laser in vitro to evaluate the effect of a pulsed alexandrite laser on antibiotic-resistant bacteria utilizing varying exposure times, pulse durations, and laser fluencies to determine which dose is more effective on S. aureus bacteria. Method: The laser used in this study was the alexandrite laser which was considered a pulsed laser and had the following parameters: The wavelength was 755 nm, the beam diameter was (14 mm), the exposure times varied (30, 60, 90) seconds, the laser fluency (5, 10, 15 and 20 J.Cm-2). The study was carried out after the bacteria were diagnosed as being antibioticresistant. They were exposed to different doses of Alexandrite laser. Three samples of bacteria were exposed to laser beams for 30 seconds with a 5ms pulse duration and with a laser fluency of 5J/cm2, and this process was repeated with laser fluencies of 10, 15, and 20. This procedure was repeated using exposure times of 60sec and 90sec. As well as, this process was repeated by exposure with 30 sec, 60 sec and 90 sec exposure times, 10ms and 20ms pulse durations and with different laser fluencies 5, 10, 15 and 20J/cm2, separately. Results: A significant reduction (p = &lt;0.0001) in the mean values of the colony was observed with the increase of laser fluency doses compared with control at the same pulse duration. A significant reduction (p = &lt;0.0001) in the mean count of the colonies was observed in the comparison between two laser fluences at the same pulse duration. In conclusion, the exposure times, pulse durations and laser fluencies of pulsed alexandrite laser showed an effect on the mean count of the colonies of S aureus bacteria and determined the effective dose. Keywords: laser, Staphylococcus aureus, Bacteria growth

Understanding ART Adherence among Adolescent Girls and Young Women in Western Kenya: A Cross-Sectional Study of Barriers and Facilitators.

HIV remains a leading cause of death for adolescent girls and young women (AGYW) in sub-Saharan Africa. This population has a high incidence of HIV and other comorbidities, such as experiencing violence, and low antiretroviral therapy (ART) adherence. To reach global HIV goals, data are needed on the specific adherence barriers for AGYW living with HIV, so interventions can be targeted effectively. Cross-sectional data were collected at urban and rural health facilities in and around Kisumu County, western Kenya, from January to June 2022, from AGYW 15-24 years of age who were living with HIV. Surveys included questions on intimate partner violence, mental health issues, food security, and orphanhood. Adherence was categorized using viral load testing where available and the Center for Adherence Support Evaluation (CASE) adherence index otherwise. Logistic regression was used to assess associations between potential explanatory variables and adherence. In total, 309 AGYW participated. AGYW with experiences of emotional violence (Odds Ratio [OR] = 1.94, 95% Confidence Interval [CI] = 1.03-3.66), moderate or severe depression (OR = 3.19, 95% CI = 1.47-6.94), and/or substance use (OR = 2.71, 95% CI = 1.24-5.92) had significantly higher odds of poor adherence when compared to AGYW without these respective experiences. Physical and sexual violence, food insecurity, and orphanhood were not associated with poor adherence in this cohort. Elucidating the risk factors associated with poor adherence among AGYW living with HIV allows us to identify potential targets for future interventions to improve ART adherence and HIV care outcomes. Mental health and violence prevention interventions, including combination interventions, may prove to be promising approaches.

Effectiveness of a workshop-based intervention to reduce bullying and violence at work: A 2-year quasi-experimental intervention study

IntroductionBullying and violence at work are associated with reduced wellbeing of the victims, but few evidence-based interventions are available to prevent these offensive behaviours. We developed and examined the effectiveness of an intervention aimed at prevention of bullying and violence at work through modifications in psychosocial work environment. MethodsIn accordance with pre-published protocol, employees and supervisors of 12 work units in 3 cities (intervention group A: n = 315; intervention group B: n = 271) received a workshop-based intervention on organizational practices to prevent bullying and violence, including supervisor support, supervisor justice, workplace social capital, and psychological safety and were compared to a reference group (n = 2310) which did not receive the intervention. Latent change score modelling (LCSM) was used to estimate between- and within-individual differences in changes of organizational practices and prevalence of bullying and violence from baseline (2020) to follow-up (2022). ResultsNo direct or indirect effects of intervention were observed. Of the potential mediator variables, supervisor support (B = 0.04; 95% confidence interval 0.006, 0.07) and supervisor justice (0.04; 0.01, 0.08) improved in the intervention group B between the measurements and compared to control group, but the result was not replicated in intervention group A. No changes were observed between the measurement points in bullying or violence at work. ConclusionsNo intervention effects on bullying and violence at work were observed. It may be worthwhile to develop the intervention further to focus more on supervisor and co-worker relationships and on psychosocial resources of work team.

Establishment and verification of prediction model of occult peritoneal metastasis in advanced gastric cancer

BackgroundTo investigate the risk factors associated with the development of occult peritoneal metastasis in advanced gastric cancer, and establish and externally validate a nomogram for predicting the occurrence of occult peritoneal metastasis in patients with advanced gastric cancer.MethodsA total of 111 patients with advanced gastric cancer who underwent laparoscopic exploration or peritoneal lavage cytology examination at the Affiliated Drum Tower Hospital of Nanjing University Medical School from August 2014 to December 2021 were retrospectively analyzed. The patients diagnosed between 2019 and 2021 were assigned to the training set (n = 64), while those diagnosed between 2014 and 2016 constituted the external validation set (n = 47). In the training set, patients were classified into two groups based on preoperative imaging and postoperative pathological data: the occult peritoneal metastasis group (OPMG) and the peritoneal metastasis negative group (PMNG). In the validation set, patients were classified into the occult peritoneal metastasis group (CY1P0, OPMG) and the peritoneal metastasis negative group (CY0P0, PMNG) based on peritoneal lavage cytology results. A nomogram was constructed using univariate and multivariate analyses. The performance of the nomogram was evaluated using Harrell’s C-index, the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and calibration plots.ResultsThis study analyzed 22 potential variables of OPM in 111 gastric cancer patients who underwent laparoscopic exploration or peritoneal lavage cytology examination. Logistic regression analysis results showed that Lauren classification, CLDN18.2 score and CA125 were independent risk factors for OPM in patients with gastric cancer. We developed a simple and easy-to-use prediction nomogram of occult peritoneal metastasis in advanced gastric cancer. This nomogram had an excellent diagnostic performance. The AUC of the bootstrap model in the training set was 0.771 and in the validation set was 0.711. This model showed a good fitting and calibration and positive net benefits in decision curve analysis. ConclusionWe have developed a prediction nomogram of OPM for gastric cancer. This novel nomogram has the potential to enhance diagnostic accuracy for occult peritoneal metastasis in gastric cancer patients.