Selection Of Candidates Research Articles

The Zimbabwe political space

Zimbabwe's post-independence election processes have been predominantly male-dominated, with women relegated to the periphery as electorates or party ‘cheerleaders’. Since the Beijing conference in 1995, Zimbabwe enacted several laws to overcome bottlenecks that have impeded women's participation in political processes, with the 2013 Constitution serving as the ultimate template for promoting women's engagement in mainstream electoral systems. Nonetheless, women’s participation as candidates or leaders in electoral processes has declined significantly since the 2013 Constitution. The study brings to the fore, findings to respond to 3 fundamental research questions which are: 1) what is the interlinkage between economic, cultural, social, and physical spaces with the electoral processes, 2) what are the complex social inclusion factors in political spaces, and 3) what recommendations can be proffered to enhance inclusion of women in electoral processes. In answering the questions, the research draws on content analysis of reports from the Project on Preventing Violence Against Women in Politics Project (VAWP/E), face-to-face interviews, and focus group discussions to offer insights and investigate the opportunities provided by various legal frameworks to increase women's engagement in electoral and political processes in Zimbabwe. The article further systematically explores other important factors and elements that impede and contribute to women's full participation in electoral processes as candidates. This study contends that the availability of excellent legal provisions does not result in increased women's participation in electoral politics as candidates unless there is political will. The study further asserts that participation in social, cultural, economic, and physical spaces interacts in a complex manner and influences women's participation in Zimbabwe's electoral political processes as candidates. Because of the country's political polarisation and the impunity of perpetrators of political violence, the political arena is believed to be intimidating and discouraging, thus not ripe, for women to participate as candidates. The study recommends a wholesome approach to dismantling the complex interlinkages between cultural, social, economic, and physical spaces as obstacles affecting the inclusion of women in electoral processes as candidates. Thus, the study further recommends that existing legal instruments should be complemented by progressively dismantling the social, cultural, and physical forces prohibiting women's participation as leaders in electoral processes. Specific provisions in the Electoral Act may further be used to penalise failure by political parties to field a reasonable number of women as candidates in elections.

The Impact of Transactional Politics on Papuan Ethnic Identity Politics in the Dynamics of the 2024 General Election in Manokwari Regency

The objective of this study is to investigate the perspectives of the Papuan ethnic group regarding the dynamics of identity politics in general elections, which frequently encompass aspirations related to identity politics. The term "Papuan ethnicity" refers to an identity within Papuan nationalism, symbolizing the mobilization and unification of Papuans. In the context of elections, the notion of Papuan ethnicity becomes a significant issue for electoral candidates, particularly for those who lack support from their fellow Papuans. Utilizing qualitative research methods and ethnographic approaches, this study explores the impact of transactional politics on the ethnic perspectives and political participation of Papuans during elections. It examines various factors, including the influence of political funding on voter preferences, the mobilization of ethnic groups for political backing, and the dynamics of inter-ethnic interactions within political disputes. The findings of this research aim to provide an in-depth understanding of the patterns of political aspirations in Papua and their implications for the consolidation of democracy in Indonesia.Keywords: identity politics, political aspirations, Papuan ethnicity, general elections

Optimizing patient selection for cardiac resynchronization therapy in a multicenter study of Japanese patients: assessment of the MADIT-ICD benefit group

Abstract Background The MADIT-ICD benefit group, derived from ventricular tachycardia (VT)/ventricular fibrillation (VF) scores and non-arrhythmic mortality scores (Table 1), facilitates the appropriate selection of candidates for implantable cardioverter-defibrillator (ICD) therapy. While the 2021 European Society of Cardiology Guidelines have discussed the advantages and considerations of adding a defibrillator in patients undergoing cardiac resynchronization therapy (CRT), the optimal selection of CRT with or without a defibrillator remains unclear, particularly in Asian populations. This is especially relevant for primary prevention using ICD, which is characterized by fewer cases of ischemic etiology compared to Western countries. Purpose This study aimed to evaluate the utility of the MADIT-ICD benefit group in Japanese CRT patients and identify key indicators for determining the necessity of CRT with or without a defibrillator. Methods We conducted a retrospective, multicenter evaluation of 505 consecutive Japanese CRT patients enrolled between 2012 and 2020. Among these patients, 76% were male, with a mean age of 65 years and a mean body mass index of 22.5 kg/m2. Ischemic etiology was present in 25% of patients, with 20% undergoing secondary prevention. The study assessed the cumulative incidences of VT/VF and non-arrhythmic mortality based on the MADIT-ICD benefit group (lowest, intermediate, and highest). Predictors for each outcome were explored, and the MADIT-ICD benefit group was validated in the Japanese cohort. Results Of the 400 included patients, 60 (15%) were categorized into the lowest MADIT-ICD benefit group, 279 (70%) into the intermediate group, and 61 (15%) into the highest group. Over a median follow-up period of 34 months, VT/VF occurred in 4 (13%), 68 (24%), and 14 (23%) patients in the lowest, intermediate, and highest benefit groups, respectively (Gray’s test, P = 0.027, Figure 1A). Non-arrhythmic death occurred in 15 (25%), 91 (33%), and 9 (15%) patients in the lowest, intermediate, and highest benefit groups, respectively (Log-rank test, P = 0.025, Figure 1B). Multivariable analysis identified MADIT-ICD VT/VF score (hazard ratio [HR] 1.23; 95% confidence interval [CI] 1.12-1.35; P < 0.001) and left bundle branch block (LBBB) (HR 0.48; 95% CI 0.27-0.86; P = 0.014) as significant predictors for VT/VF, while MADIT-ICD non-arrhythmic mortality score (HR 1.16; 95% CI 1.07-1.27; P < 0.001), serum creatinine (Cr) (HR 1.28; 95% CI 1.13-1.45; P < 0.001), and mineral corticoid receptor antagonist (MRA) use (HR 1.84; 95% CI 1.21-2.79; P = 0.004) were significant predictors for non-arrhythmic death (Table 2). Conclusion The MADIT-ICD benefit group, in conjunction with left bundle branch block and renal function, may serve as valuable predictors for determining the necessity of cardioverter-defibrillator therapy in Japanese CRT patients.Table 1 and Figure 1

Impact of left atrial stiffness measurement as a pre-procedural predictor of an extensive left atrial low-voltage area

Abstract Background The presence of a left atrial (LA) low-voltage area (LVA) after pulmonary vein isolation for atrial fibrillation (AF) is a strong predictor of recurrence and LVAs are often an additional ablation target. However, predicting the presence of an LVA before the procedure remains challenging. Purpose To assess the LA stiffness index as a preprocedural predictor of an extensive LVA. Methods We prospectively evaluated 74 patients who underwent catheter ablation for AF and high-density bipolar LA voltage mapping during sinus rhythm or high right atrial pacing. "LVA" was defined as an area with bipolar electrograms (<0.5 mV), while "extensive LVA" was defined as the presence of an LVA that covered more than 15% of the LA surface. Echocardiographic measurements, including the LA volume index (LAVi), E/e' ratio, LA reservoir strain (LASr), and LA stiffness index, calculated as the ratio of E/eʹ to LASr, were performed prior to catheter ablation in all patients. Results Overall, 17 patients (23.0%) had an extensive LVA. Patients with extensive LVAs were older (73 ± 7 vs. 66 ± 8 years; P=0.003), predominantly female (59% vs. 23%; P=0.01), and more frequently showed persistent AF (59% vs. 30%; P=0.04) in comparison to patients without extensive LVAs. According to a receiver operating characteristic curve analysis, the LA stiffness index was more accurate than the LAVi or LASr for predicting extensive LVAs (Figure), allowing using a cutoff value ≥0.6 with 73% sensitivity and 91% specificity. A multivariate logistic regression analysis revealed that the LA stiffness index was an independent predictor of an extensive LVA (odds ratio [OR], 44.11; 95% CI 3.83–507.47, P=0.002). Conclusion The LA stiffness index was a robust predictor of the extent of LVAs in AF patients and thus could be useful for the preprocedural selection of candidates for catheter ablation and to determine the most effective ablation strategies.

Predictors of Right vEntricular Failure aftER LVAD implantation: PREFER LVAD study

Abstract Introduction The use of left ventricular assist devices (LVAD) is increasing both as bridge-to-transplantation or destination therapy, considering the lack of heart donors for transplantation in advanced heart failure (AHF) population. Right ventricular post-implantation failure, major bleedings and infective events remain the principal adverse events in LVAD carriers, thus an accurate selection of candidates is needed. Purpose To identify between clinical, laboratory, standard and advanced (Speckle Tracking, STE) echocardiography, and right heart catheterization (RHC) indices, the best predictors of outcome after LVAD implantation. Materials and Methods We screened in our third-level center 30 patients with AHF, followed up from May 2013 to February 2022, for the assessment of LVAD implantation suitability. They all underwent a complete cardiological history collection, electrocardiography, standard and STE left ventricular (LV) and left atrial (LA) size and function assessment. Regarding the right ventricle, SIENA score parameters, including RV sphericity index, RV free wall longitudinal strain (LS), right ventricular fractional area change (RVFAC), and 3D ejection fraction were used for exclude RV disfunction. RHC was performed on the same day of echocardiography. Follow-up was conducted at 1, 3, 6, 9 and 12 months repeating all the assessments, for the occurrence of RV failure, all-causes mortality, hemorrhagic events and re-hospitalization for heart failure. With a univariate and multivariate statistical analysis, we went to test among all the parameters the possible predictors of outcome. Results The final population consists of 29 patients (93% male, mean age of 63±11 years), in NYHA class III or IV and a severe reduction of left ventricular (LV) ejection fraction (EF), in whom arterial hypertension and smoking, present or previous, were present in 58% and 65% of cases, respectively. The population was divided into two groups according to the occurrence of at least one cardiovascular event. 11 major events were recorded: including 4 hemorrhagic events, 3 all-causes mortality and 4 hospital admission for HF. No RV failure occurred in the first 12 months of follow-up. No differences were identified between the two groups in terms of echocardiographic indices and RV function, including RVFAC or RV-FWLS. At univariate analysis (see Table 1), the only parameter able to predict major CV events was central venous pressure (CVP)/pulmonary capillary wedge pressure (PCWP) ratio, obtained by RHC, an index of balance between right and left heart filling pressure. Conclusions A careful application of SIENA score indices before LVAD implantation can significantly reduce the incidence of post-operative RV failure, as in our small population. Our results also confirmed the paramount role of RHC in the diagnostic work up of AHF.

Is extended resection for locally advanced thoracic cancer with cardiopulmonary bypass justified?

BackgroundResection of intrathoracic tumor with cardiopulmonary bypass (CPB) remains a relatively under-reported intervention in literature, and its role in managing locally advanced mediastinal and lung cancers is a topic of ongoing debate. Our aim was to review our experience and assess the role of CPB for treating locally advanced mediastinal and lung cancers.MethodsBetween 2015 and 2020, this study initially included 10 patients with primary locally advanced thoracic malignancies with apparent adjacent cardiovascular invasion demonstrated by thoracic imaging scans. Operation was performed based on a multidisciplinary tumor board consensus. Eventually, 8 patients (3 primary lung cancers and 5 mediastinal cancers) received either salvage or elective resection with CPB; two completed surgery without requiring CPB.ResultsRegarding the extent of adjacent structure involvement, 4 patients presented with involvement of the superior vena cava (SVC), 1 involved the right atrium (RA), 2 involved the SVC and RA, and 1 involved the SVC, the origin of main pulmonary artery, and the ascending aorta. Thirty-day mortality occurred in two of three patients receiving salvage surgery due to respiratory insufficiency. With the long-term follow-up, one patient died of recurrence 25 months postoperatively, one survived with recurrence 30 months postoperatively, and four were alive without recurrence for 35, 36, 49, and 107 months after operations.ConclusionIn certain patients, particularly for elective surgical candidates rather than salvage resection, CPB allows for extended resection of locally advanced thoracic cancers with acceptable perioperative safety and survival.

Advancing Organizational Effectiveness Through Strategic Workforce Planning and Technology Integration

Abstract: This comprehensive examination delves into the pivotal roles of strategic workforce planning and technological advancements in bolstering organizational effectiveness. Spanning various critical dimensions such as human resource demand forecasting, strategic recruitment and selection, employee training and development, diversity and inclusivity, and the integration of technology in HR practices, the paper articulates a multi-faceted approach to optimizing workforce capabilities. By leveraging predictive analytics, organizations can forecast future employment needs, while AI-enhanced recruitment processes streamline candidate selection, ensuring alignment with organizational goals. The deployment of advanced training methodologies, coupled with a focus on creating a diverse and inclusive work environment, not only enriches organizational culture but also drives innovation and improves overall performance. The paper further explores the strategic use of HR analytics, AI in recruitment, and digital platforms in employee development and engagement, highlighting their significance in adapting to the evolving work landscape. Through an in-depth analysis, it becomes evident that the integration of strategic HR planning and cutting-edge technologies is not merely an option but a necessity for organizations aiming to thrive in the competitive global market.

Personality profiles of 263 occupations.

While personality trait assessments are widely used in candidate selection, coaching, and occupational counseling, little published research has systematically compared occupations in personality traits. Using a comprehensive personality assessment, we mapped 263 occupations in self-reported Big Five domains and various personality nuances in a sample of 68,540 individuals and cross-validated the findings in informant ratings of 19,989 individuals. Controlling for age and gender, occupations accounted for 2%-7% of Big Five variance in both self-reports and informant reports. Most occupations' average Big Five levels were intuitive, replicated across rating methods, and were consistent with those previously obtained with a brief assessment in a different sociocultural context. Often, they also tracked the Occupational Information Network database's work style ratings and clustered along the International Standard Classification of Occupation's hierarchical framework. Finally, occupations with higher average levels of the personality domains typically linked to better job performance tended to be more homogeneous in these domains, suggesting that jobs with higher performing incumbents are often more selective for personality traits. Several personality nuances had intuitive occupational differences that were larger than those of the Big Five domains (explaining up to 12% variance) and replicated well across rating methods, providing more detailed insights into how job incumbents vary in personality. We provide an interactive application for exploring the results (https://apps.psych.ut.ee/JobProfiles/) and discuss the findings' theoretical and practical implications. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Nomogram Predictive Model for Vaginal Birth after One Prior Cesarean Section: A Retrospective Study

Background: Repeat cesareans pose significant maternal risks, whereas vaginal birth after cesarean (VBAC) offers better outcomes, with a complication rate of 2.4% compared with 3.6% for elective repeat cesareans and 14.1% for failed trial of labor after cesarean (TOLAC). TOLAC rates are low in China, and success rates vary between 60% and 80%. This study aims to develop a nomogram-based predictive model for VBAC in China and improve existing, less rigorous scoring models. Methods: This retrospective cohort study was conducted at Hangzhou Women's Hospital from February 2015 to March 2020, and included 159 parturient attempts at labor after one prior low transverse cesarean section. The participants were divided into two groups based on their mode of delivery for comparison: the VBAC and the TOLAC failure group. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors for VBAC and develop a nomogram predictive model to estimate the success rate of TOLAC. The bootstrap method was used for internal validation of the models. Three different VBAC prediction models were evaluated by plotting receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results: A total of 127 women had VBAC and 32 women failed TOLAC, with a success rate of 79.9%. Three independent factors affecting the VBAC were identified: gestational age at delivery, Bishop score and newborn birth weight. A predictive nomogram model for the VBAC was constructed that incorporates these three factors. The model showed a good fit (χ2 = 11.94, p = 0.154) with an overall prediction accuracy of 81.1%. The area under the ROC curve was 0.83 (95% CI (confidence interval), 0.76–0.90) (p < 0.001) and the optimal cut-off value was 83.4%. The bootstrap internal validation showed that our predictive model maintained high overall accuracy and specificity, but exhibited low sensitivity and a low Kappa coefficient. Compared to the Grobman model and Jiaming Rao et al. model, our developed prediction model possesses the strongest discriminatory ability and the highest net benefit, followed by the model by Jiaming Rao et al. All three models demonstrate a high degree of fit. Conclusions: Shorter gestational age at delivery, lower newborn birth weight and higher cervical Bishop score are favorable factors for VBAC. The predictive nomogram model for the VBAC after a single cesarean section, constructed with these three factors, has good predictive efficacy. The model is simple to calculate and has practical value in the clinical selection of suitable candidates for TOLAC after a single cesarean section.

Heart Rate Recovery Index and Improved Diastolic Dyssynchrony in Fusion Pacing Cardiac Resynchronization Therapy.

Background: Restoring electrical synchrony with cardiac resynchronization therapy (CRT) reverses the heart failure phenotype developed by left-ventricular (LV) dyssynchrony. This study aimed to identify new predictors of response to LV-only fusion pacing CRT. Methods: A select group of patients with CRT-P indications received a right atrium (RA)/LV DDD pacing system. LV dyssynchrony was assessed via offline TDI timing focusing on the temporal difference between peak septal (E″T) and lateral wall (A"T) motion. CRT effectiveness was evaluated at each follow-up, involving the heart rate recovery index (HRRI) parameter (acceleration/deceleration time) derived from exercise testing along with the echocardiographic parameters. Patients were classified into super-responders (SR), responders (R), and non-responders (NR). Results: Baseline initial characteristics: 62 patients (35 male) aged 62 ± 11 y.o. with non-ischemic dilated cardiomyopathy (DCM). Ejection fraction (EF) 27 ± 5.2%; QRS 164 ± 18 ms; 29% had type III diastolic dysfunction (DD), 63% type II DD, and 8% type I DD. Average follow-up was 45 ± 19 months: 34% of patients were SR, 61% R, and 5% NR. The E″T decreased from 90 ± 20 ms to 25 ± 10 ms in SR, with a shorter deceleration time (DT) during exercise test compared to NR (109 ± 68 ms vs. 330 ± 30 ms; p < 0.0001). The responders present a higher HRRI (2.87 ± 1.47 vs. 0.98 ± 0.08; p = 0.03) compared to NR and a significantly decrease in E"T and A"T from 76 ± 13 ms to 51 ± 11 ms (p < 0.0001). Prolonged DT was associated with an accentuated LV dyssynchrony and nonoptimal response to CRT. Conclusions: The study identified new parameters for assessing responsiveness to LV-only fusion pacing CRT, which could improve candidate selection and CRT implementation.

Liver Transplantation for the Cure of Neuroendocrine Liver Metastasis: A Systematic Review with Particular Attention to the Risk Factors of Death and Recurrence

Background/Objectives: Neuroendocrine neoplasms (NEN) are heterogeneous entities. Despite considerable advancement in the field, almost 50% of patients have metastatic disease, when liver transplantation (LT) is one of the possible treatments offering a cure in well-selected patients. Methods: The present study aims to systematically review all the literature from 2000 onwards on using LT for patients with NEN-LM, with particular attention to the risk factors of death and recurrence. Results: LT offers 5-year OS ranging from 52 to 74% and 5-year TFS rates ranging from 39 to 62%, with even better results published from 2009 onwards. The main risk factors for patient deaths are related to unfavorable primary tumor pathology, higher liver involvement, and simultaneous LT and primary resection. Similarly, recurrence is higher related to poor tumor grade and differentiation, and in the case of an older recipient age. Conclusions: Applying uniform criteria and a more in-depth understanding of the relevant prognostic factors contribute to a better selection of candidates for curative LT due to NEN metastases. LT for unresectable or liver-restricted NENs has a relevant place in the treatment algorithm and has achieved excellent results in recent decades, but more international efforts are needed to further improve outcomes.

Hot node limitations and impact of taxonomic resolution on phylogenetic divergence patterns: A case study on Ecuadorian ethnomedicinal flora

SummarySocietal Impact StatementNovel phylogenetic approaches have emerged in recent years to study traditional medicinal plants, aiming to identify potential sources of new drugs. This line of research holds considerable promise yet remains in its early stages. Here, we examine the prevalent methods employed in the field, revealing the impact of methodological choices that have often been made arbitrarily. We also highlight a widespread misconception regarding ‘hot node analysis’, a tool gaining popularity for identifying plants with high bioactive potential. Our findings should advance future research aimed at guiding the selection of promising candidates for bioprospection.Summary Advances in phylogenetics offer a ground‐breaking approach to analysing ethnobotanical data. This line of research typically involves calculating the degree of phylogenetic clustering (i.e. phylogenetic divergence) of a set of medicinal plants and identifying clades with a significant overabundance of these plants, known as hot nodes, which are purportedly responsible for the clustering patterns. However, despite showing great promise, the adequacy of this procedure remains to be tested, and the results have so far been inconclusive and, at times, contradictory. Here, we examine two key elements through a case study of Ecuadorian medicinal flora: the impact of taxonomic resolution (species‐ and genus‐level data) on phylogenetic divergence metrics (Mean Pairwise Distance; MPD, and Mean Nearest Taxon Distance; MNTD), and the efficacy of the hot node analysis in identifying clades that significantly influence these metrics. To identify clades with a significant impact on MPD and MNTD, we implemented a jackknifing procedure and compared outcomes with the hot nodes. Phylogenetic divergence was strongly dependent on the taxonomic resolution, with clustering mainly revealed by MPD at the genus level. Further, the hot nodes incompletely matched those with significant influence on MPD and MNTD according to the jackknifing analysis. We highlight the impact of taxonomic resolution on commonly used phylogenetic divergence metrics and the limitations of hot nodes in identifying influential clades, stressing the potential of alternative jackknifing techniques. We recommend the use of the most resolved tree possible and combining jackknifing with hot node analyses as complementary sources to pinpoint clades for bioprospection.

Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle

BackgroundAfrican cattle represent a unique resource of genetic diversity in response to adaptation to numerous environmental challenges. Characterising the genetic landscape of indigenous African cattle and identifying genomic regions and genes of functional importance can contribute to targeted breeding and tackle the loss of genetic diversity. However, pinpointing the adaptive variant and determining underlying functional mechanisms of adaptation remains challenging.ResultsIn this study, we use selection signatures from whole-genome sequence data of eight indigenous African cattle breeds in combination with gene expression and quantitative trait loci (QTL) databases to characterise genomic targets of artificial selection and environmental adaptation and to identify the underlying functional candidate genes. In general, the trait-association analyses of selection signatures suggest the innate and adaptive immune system and production traits as important selection targets. For example, a large genomic region, with selection signatures identified for all breeds except N’Dama, was located on BTA27, including multiple defensin DEFB coding-genes. Out of 22 analysed tissues, genes under putative selection were significantly enriched for those overexpressed in adipose tissue, blood, lung, testis and uterus. Our results further suggest that cis-eQTL are themselves selection targets; for most tissues, we found a positive correlation between allele frequency differences and cis-eQTL effect size, suggesting that positive selection acts directly on regulatory variants.ConclusionsBy combining selection signatures with information on gene expression and QTL, we were able to reveal compelling candidate selection targets that did not stand out from selection signature results alone (e.g. GIMAP8 for tick resistance and NDUFS3 for heat adaptation). Insights from this study will help to inform breeding and maintain diversity of locally adapted, and hence important, breeds.

Descriptive Representation and Reproductive Health Outcomes: The Role of Women Candidates in Reducing Teen Birth Rates.

Teen birth rates remain a pressing public health issue in the United States, with significant long-term health risks for both mothers and children. Previous research has primarily focused on the impact of women in elected office on reproductive health outcomes, but less is known about the influence of women candidates. This study explores the relationship between the number of women candidates in county-level elections and county-level teen birth rates, highlighting the role of women candidates as visible role models and agents of potential policy change. We utilized a dataset covering county-level elections from 2010 to 2020, along with teen birth rate data from the CDC. We employed a multilevel model to analyze the relationship between the cumulative number of women candidates and teen birth rates, controlling for socioeconomic and health-related factors, such as insurance coverage and social vulnerability. The findings indicate that as the number of women candidates increased, the estimated county-level teen birth rate declined. This effect was observed across different election years, with more substantial impacts in midterm and presidential elections. The analysis also confirmed that socioeconomic conditions, such as a lack of health insurance, contribute to higher teen birth rates. Women candidates, even when not elected, serve as important role models and influence reproductive health outcomes in their communities. Increasing the number of women candidates at the local level may be an effective strategy for reducing teen birth rates and improving public health outcomes.

Phosphatidylethanol testing and return to alcohol use after liver transplantation: Implications for candidate selection and care.

Phosphatidylethanol testing and return to alcohol use after liver transplantation: Implications for candidate selection and care.

Muscle Mass and Glucagon-Like Peptide-1 Receptor Agonists: Adaptive or Maladaptive Response to Weight Loss?

Recent studies have shown that pharmacologic weight loss with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and combination therapies is approaching magnitudes achieved with surgery. However, as more weight loss is achieved, there is concern for potential adverse effects on muscle quantity, composition, and function. This primer aims to address whether muscle-related changes associated with weight loss treatments such as GLP-1 RAs may be maladaptive (ie, adversely affecting muscle health or function), adaptive (ie, a physiologic response to weight loss maintaining or minimally affecting muscle health or function), or perhaps an enhanced response to weight loss (ie, improved muscle health or function after treatment). Based on contemporary evidence with the addition of studies using magnetic resonance imaging, skeletal muscle changes with GLP-1 RA treatments appear to be adaptive: changes in muscle volume z-score indicate a change in muscle volume that is commensurate with what is expected given aging, disease status, and weight loss achieved, and the improvement in insulin sensitivity and muscle fat infiltration likely contributes to an adaptive process with improved muscle quality, lowering the probability for loss in strength and function. Nevertheless, factors such as older age and prefrailty may influence the selection of appropriate candidates for these therapies because of risk for sarcopenia. Several pharmacologic treatments to maintain or improve muscle mass designed in combination with GLP-1-based therapies are under development. For future development of GLP-1-based therapies (and other therapies) designed for weight loss, as well as for patient-centered treatment optimization, the introduction of more objective and comprehensive ways of assessing muscle health (including accurate and meaningful assessments of muscle quantity, composition, function, mobility, and strength) is important for the substantial numbers of patients who will likely be taking these medications well into the future.

Isolation and characterization of mung bean (Vigna radiata L.) rhizobia in Myanmar

AbstractWe collected soil samples from six major mung bean cropping regions in Myanmar: Sagaing, Mandalay, Nay Pyi Taw, and Magway in the tropical savanna climate zone and Bago and Yangon in the tropical monsoon climate zone. All fields grew mung bean for at least 5 years and had no history of rhizobial inoculation. Mung bean ‘Yezin-11’, a popular cultivar in Myanmar, was inoculated with soil suspensions. From the nodules formed on the roots, we isolated 55 rhizobial strains. Identification of the isolates revealed the dominant species of indigenous rhizobia in each region. We identified 53 Bradyrhizobium strains and 2 Ensifer strains. Bradyrhizobium yuanmingense was dominant in the tropical savanna zone and Bradyrhizobium sp. (B. liaoningense or B. diversitatis) and B. centrosematis were dominant in the tropical monsoon zone. Principal component analysis indicates that the dominance of B. yuanmingense in the tropical savanna zone might be due to high concentration of NO3-N and P2O5 in the soil. It also indicates that the dominance of B. centrosematis in the tropical monsoon zone might be caused by drastically low pH and high concentration of NH4 in the soil. Bradyrhizobium centrosematis YGN-M9, B. yuanmingense SGG-M3, and Bradyrhizobium sp. BGO-M5 significantly increased nodulation (nodule number and nodule dry weight), acetylene reduction activity, and shoot dry weight, respectively, relative to Ensifer terangae MDY-M6. Co-inoculation with these three strains increased nodulation significantly compared with single inoculation of BGO-M5. The characterization of mung bean rhizobia and selection of microbial inoculant candidates will be useful for the development of microbial inoculants in Myanmar.

The presence of a ghost infarct core is associated with fast core growth in acute ischemic stroke.

The overestimation of ischemic core volume by CT perfusion (CTP) is a critical concern in the selection of candidates for reperfusion therapy. This phenomenon is termed a ghost infarct core (GIC). Core growth rate (CGR) is an indicator of ischemic severity. We aimed to elucidate the association between GIC and CGR. Consecutive patients with acute ischemic stroke who underwent mechanical thrombectomy in our institute from March 2017 to July 2022 were enrolled. The initial ischemic core volume (IICV) was measured by pretreatment CTP, and the final infarct volume (FIV) was measured by diffusion-weighted imaging. A GIC was defined by IICV minus FIV > 10 ml. The CGR was calculated by dividing the IICV by the time from onset to CTP. Univariable analysis and a multivariable logistic regression model were used to evaluate the association between GIC-positive and CGR. Of all 91 patients, 21 (23.1%) were GIC-positive. The GIC-positive group had higher CGR (14.2 [2.6-46.7] vs 4.8 [1.6-17.1] ml/h, p = 0.02) and complete recanalization (n = 15 (71.4%) vs 29 (41.4%), p = 0.02) compared to the GIC-negative group. On receiver-operating characteristic curve analysis, the optimal cutoff point of CGR to predict GIC-positive was 22 ml/h (sensitivity, 0.48; specificity, 0.85; AUC, 0.67). Multivariable logistic regression analysis showed that CGR ⩾ 22 ml/h (OR 6.44, 95% CI [1.59-26.10], p = 0.01) and complete recanalization (OR 3.72, 95% CI [1.14-12.08], p = 0.02) were independent predictors of GIC-positive. A GIC was associated with fast CGR in acute ischemic stroke. Overestimation of the initial ischemic core may be determined by core growth speed.

Integrating Molecular Dynamics and Machine Learning Algorithms to Predict the Functional Profile of Kinase Ligands.

The modulation of protein function via designed small molecules is providing new opportunities in chemical biology and medicinal chemistry. While drugs have traditionally been developed to block enzymatic activities through active site occupation, a growing number of strategies now aim to control protein functions in an allosteric fashion, allowing for the tuning of a target's activation or deactivation via the modulation of the populations of conformational ensembles that underlie its function. In the context of the discovery of new active leads, it would be very useful to generate hypotheses for the functional impact of new ligands. Since the discovery and design of allosteric modulators (inhibitors/activators) is still a challenging and often serendipitous target, the development of a rapid and robust approach to predict the functional profile of a new ligand would significantly speed up candidate selection. Herein, we present different machine learning (ML) classifiers to distinguish between potential orthosteric and allosteric binders. Our approach integrates information on the chemical fingerprints of the ligands with descriptors that recapitulate ligand effects on protein functional motions. The latter are derived from molecular dynamics (MD) simulations of the target protein in complex with orthosteric or allosteric ligands. In this framework, we train and test different ML architectures, which are initially probed on the classification of orthosteric versus allosteric ligands for cyclin-dependent kinases (CDKs). The results demonstrate that different ML methods can successfully partition allosteric versus orthosteric effectors (although to different degrees). Next, we further test the models with FDA-approved CDK drugs, not included in the original dataset, as well as ligands that target other kinases, to test the range of applicability of these models outside of the domain on which they were developed. Overall, the results show that enriching the training dataset with chemical physics-based information on the protein-ligand dynamic cross-talk can significantly expand the reach and applicability of approaches for the prediction and classification of the mode of action of small molecules.

Drug Repurposing for Effective Alzheimer's Disease Medicines: Existing Methods and Novel Pharmacoepidemiological Approaches.

Drug repurposing is a methodology used to identify new clinical indications for existing drugs developed for other indications and has been successfully applied in the treatment of numerous conditions. Alzheimer's disease (AD) may be particularly well-suited to the application of drug repurposing methods given the absence of effective therapies and abundance of multi-omic data that has been generated in AD patients recently that may facilitate discovery of candidate AD drugs. A recent focus of drug repurposing has been in the application of pharmacoepidemiologic approaches to drug evaluation. Here, real-world clinical datasets with large numbers of patients are leveraged to establish observational efficacy of candidate drugs for further evaluation in disease models and clinical trials. In this review, we provide a selected overview of methods for drug repurposing, including signature matching, network analysis, molecular docking, phenotypic screening, semantic network, and pharmacoepidemiological analyses. Numerous methods have also been applied specifically to AD with the aim of nominating novel drug candidates for evaluation. These approaches, however, are prone to numerous limitations and potential biases that we have sought to address in the Drug Repurposing for Effective Alzheimer's Medicines (DREAM) study, a multi-step framework for selection and validation of potential drug candidates that has demonstrated the promise of STAT3 inhibitors and re-evaluated evidence for other drug candidates, such as phosphodiesterase inhibitors. Taken together, drug repurposing holds significant promise for development of novel AD therapeutics, particularly as the pace of data generation and development of analytical methods continue to accelerate.