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Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a–nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic–eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Career Decisions of Indian Female Talent: Implications for Gender-sensitive Talent Management
(2020)
Purpose: Talent scarcity in emerging economies such as India poses challenges for companies,and limited labour market participation among well-educated women has been observed. The reasons that professionals decide not to pursue a further corporate career remain unclear. By investigating career decision making, this article aims to highlight (1) the contextual factors that impact those decisions, (2) individuals’ agency to handle them, and (3) the implications for talent management (TM).
Design/methodology/approach: Following a qualitative research design, computer-aided analysis was conducted on interviews with 24 internationally experienced Indian business professionals. A novel application of neo-institutionalism in the Indian context was combined with the family-relatedness of work decisions (FRWD) model.
Findings: Career decisions indicate that rebellion against Indian societal and family expectations is essential to following a career path, especially for women. TM as part of the current institutional framework serves as a legitimising façade veiling traditional practices that hinder females’ careers.
Research limitations: Interviewees adopted a retrospective perspective when describing their career decisions; therefore, different views might have existed at the moment of decision making.
Practical implications: Design and implementation of gender-sensitive TM adjusted to fit the specific Indian context can contribute to retaining female talent in companies and the labour market.
Originality/value: The importance of gender-sensitive TM can be concluded from an empirical study of the context-based career decision making of experienced business professionals from India. The synthesis of neo-institutionalism, the FRWD model and the research results provides assistance in mapping talent experiences and implications for overcoming the challenges of talent scarcity in India.
Background/Aim
This study aimed to establish the somatosensory profile of patients with lumbar radiculopathy at pre-and post-microdiscectomy and to explore any association between pre-surgical quantitative sensory test (QST) parameters and post-surgical clinical outcomes.
Methods
A standardized QST protocol was performed in 53 patients (mean age 38 ± 11 years, 26 females) with unilateral L5/S1 radiculopathy in the main pain area (MPA), affected dermatome and contralateral mirror sites and in age- and gender-,and body site-matched healthy controls. Repeat measures at 3 months included QST, the Oswestry Disability Index (ODI) and numerous other clinical measures; at 12 months, only clinical measures were repeated. A change <30% on the ODI was defined as ‘no clinically meaningful improvement’.
Results
Patients showed a significant loss of function in their symptomatic leg both in the dermatome (thermal, mechanical, vibration detection p < .002), and MPA (thermal, mechanical, vibration detection, mechanical pain threshold, mechanical pain sensitivity p < .041) and increased cold sensitivity in the MPA (p < .001). Pre-surgical altered QST parameters improved significantly post-surgery in the dermatome (p < .018) in the symptomatic leg and in the MPA (p < .010), except for thermal detection thresholds and cold sensitivity. Clinical outcomes improved at 3 and 12 months (p < .001). Seven patients demonstrated <30% change on the ODI at 12 months. Baseline loss of function in mechanical detection in the MPA was associated with <30% change on the ODI at 12 months (OR 2.63, 95% CI 1.09–6.37, p = .032).
Conclusion
Microdiscectomy resulted in improvements in affected somatosensory parameters and clinical outcomes. Pre-surgical mechanical detection thresholds may be predictive of clinical outcome.
Significance
This study documented quantitative sensory testing (QST) profiles in patients with lumbar radiculopathy in their main pain area (MPA) and dermatome pre- and post-microdiscectomy and explored associations between QST parameters and clinical outcome. Lumbar radiculopathy was associated with loss of function in modalities mediated by large and small sensory fibres. Microdiscectomy resulted in significant improvements in loss of function and clinical outcomes in 85% of our cohort. Pre-surgical mechanical detection thresholds in the MPA may be predictive of clinical outcome.
Abstract
Background
The clinical presentation of neck-arm pain is heterogeneous with varying underlying pain types (nociceptive/neuropathic/mixed) and pain mechanisms (peripheral/central sensitization). A mechanism-based clinical framework for spinally referred pain has been proposed, which classifies into (1) somatic pain, (2) neural mechanosensitivity, (3) radicular pain, (4) radiculopathy and mixed pain presentations. This study aims to (i) investigate the application of the clinical framework in patients with neck-arm pain, (ii) determine their somatosensory, clinical and psychosocial profile and (iii) observe their clinical course over time.
Method
We describe a study protocol. Patients with unilateral neck-arm pain (n = 180) will undergo a clinical examination, after which they will be classified into subgroups according to the proposed clinical framework. Standardized quantitative sensory testing (QST) measurements will be taken in their main pain area and contralateral side. Participants will have to complete questionnaires to assess function (Neck Disability Index), psychosocial factors (Tampa Scale of Kinesiophobia, Pain Catastrophizing Scale, Depression, anxiety and stress scale), neuropathic pain (Douleur Neuropathique 4 Questions, PainDETECT Questionnaire) and central sensitization features (Central Sensitization Inventory). Follow-ups at three, six and 12 months include the baseline questionnaires. The differences of QST data and questionnaire outcomes between and within groups will be analyzed using (M)AN(C)OVA and/or regression models. Repeated measurement analysis of variance or a linear mixed model will be used to calculate the differences between three, six, and 12 months outcomes. Multiple regression models will be used to analyze potential predictors for the clinical course.
Conclusion
The rationale for this study is to assess the usability and utility of the proposed clinical framework as well as to identify possible differing somatosensory and psychosocial phenotypes between the subgroups. This could increase our knowledge of the underlying pain mechanisms. The longitudinal analysis may help to assess possible predictors for pain persistency.