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Background: Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using "automated modelling pipelines"., Methods: Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter "feature sets": GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the "features" (independent variables) used in models., Results: Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting)., Conclusions: Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing., (© 2022. The Author(s).)

The COVID-19 pandemic could have major effects on already vulnerable individuals with psychiatric disorders. It is important to assess how different patient groups respond to stress related to the pandemic, and what additional factors influence it, including family-related stress, migration background, and sex. We conducted a survey in a sample of 294 psychiatric patients in a large outpatient clinic in Berlin, measuring level of distress in relation to COVID-19 lockdown as well as family-related distress. We also measured potential influencing factors such as media consumption and medical support. In the migration background group, we found that women had more lockdown related psychological distress than men. This was not apparent in those patients with a German background. We found that females were more strongly affected by family-related distress, particularly those with a migration background. People with PTSD were most strongly affected by family-related distress, whereas people with psychotic disorders and addiction reported the least distress. There were no effects of media consumption. There were no differences in ability to abide by the lockdown related restrictions across diagnoses. Our results support earlier findings on differential vulnerability of diagnostic groups to these stressors. Thus, clinicians can optimize treatment by taking family-related stressors into account particularly for females and people with a migrant background., Competing Interests: 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. The reviewer SW declared a shared affiliation, though no other collaboration, with the authors JM, JB, JW, SG, EB, MS-O, to the handling editor., (Copyright © 2021 Moran, Bretz, Winkler, Gutwinski, Brandl and Schouler-Ocak.)

Dysregulation of cyclin-dependent kinase 4 (CDK4) and CDK6 by gain of function or loss of inhibition is common in human cancer, including multiple myeloma, but success in targeting CDK with broad-spectrum inhibitors has been modest. By selective and reversible inhibition of CDK4/CDK6, we have developed a strategy to both inhibit proliferation and enhance cytotoxic killing of cancer cells. We show that induction of prolonged early-G(1) arrest (pG1) by CDK4/CDK6 inhibition halts gene expression in early-G(1) and prevents expression of genes programmed for other cell-cycle phases. Removal of the early-G(1) block leads to S-phase synchronization (pG1-S) but fails to completely restore scheduled gene expression. Consequently, the IRF4 protein required to protect myeloma cells from apoptosis is markedly reduced in pG1 and further in pG1-S in response to cytotoxic agents, such as the proteasome inhibitor bortezomib. The coordinated loss of IRF4 and gain of Bim sensitize myeloma tumor cells to bortezomib-induced apoptosis in pG1 in the absence of Noxa and more profoundly in pG1-S in cooperation with Noxa in vitro. Induction of pG1 and pG1-S by reversible CDK4/CDK6 inhibition further augments tumor-specific bortezomib killing in myeloma xenografts. Reversible inhibition of CDK4/CDK6 in sequential combination therapy thus represents a novel mechanism-based cancer therapy.

Inhibition of Cdk4/Cdk6 by p18(INK4c) (p18) is pivotal for generation of noncycling immunoglobulin (Ig)-secreting plasma cells (PCs). In the absence of p18, CD138(+) plasmacytoid cells continue to cycle and turnover rapidly, suggesting that p18 controls PC homeostasis. We now show that p18 selectively acts in a rare population of rapidly cycling CD138(hi)/B220(hi) intermediate PCs (iPCs). While retaining certain B-cell signatures, iPCs are poised to differentiate to end-stage PCs although the majority undergo apoptosis. p18 is dispensable for the development of the PC transcriptional circuitry, and Blimp-1 and Bcl-6 are expressed fully and mutually exclusively in individual iPCs. However, a minor proportion of iPCs express both, and they are preferentially protected by p18 or Bcl-xL overexpression, consistent with expansion of the iPC pool by Bcl-xL overexpression, or loss of proapoptotic Bim or Noxa. Expression of Noxa is induced during B-cell activation, peaks in iPCs, and selectively repressed by p18. It is required to promote apoptosis of cycling B cells, especially in the absence of p18. These findings define the first physiologic function for Noxa and suggest that by repressing Noxa, induction of G₁ arrest by p18 bypasses a homeostatic cell-cycle checkpoint in iPCs for PC differentiation.

The central conserved region of the Pseudomonas syringae hrp pathogenicity island encodes a type III protein secretion system (TTSS) that is required for pathogenicity in plants. Expression of the hrp TTSS is controlled by the alternative sigma factor, HrpL, whose expression, in turn, is positively controlled by two truncated enhancer binding proteins, HrpR and HrpS. Although a number of environmental conditions are known to modulate hrp TTSS expression, such as stringent conditions and pathogenesis, the mechanism by which the activities of these transcriptional factors are modulated had not been established. In this study, HrpR and HrpS were found to be constitutively expressed under conditions in which the hrpL promoter was inactive. To identify a postulated negative regulator of hrpL expression, transposome (Tz) mutagenesis was used to isolate hrp constitutive mutants. P. syringae Pss61 and DC3000 hrp constitutive mutants were identified that carried lon::Tz insertions and exhibited increased cell length and UV sensitivity typical of Delta lon mutants. The P. syringae Lon protease retained structural features of its homologues found in other bacteria and was capable of complementing an Escherichia coli Delta lon mutant. P. syringae lon::Tz mutants exhibited enhanced expression of the hrpL promoter, suggesting an effect on HrpR and/or HrpS. HrpR was observed to be unstable in wild-type P. syringae strains grown in non-inductive media. However, the apparent half-life increased more than 10-fold in the P. syringae lon::Tz mutants or upon transfer to an inductive medium. The P. syringae lon mutants elicited rapidly developing plant responses and were shown to hypersecrete effector proteins, such as AvrPto. These results indicate that expression of the hrp regulon and type III secretion are negatively regulated by Lon-mediated degradation of HrpR.

In Pseudomonas syringae strains, the hrp-hrc pathogenicity island consists of an HrpL-dependent regulon that encodes a type III protein translocation complex and translocated effector proteins required for pathogenesis. HrpR and HrpS function as positive regulatory factors for the hrpL promoter, but their mechanism of action has not been established. Both HrpR and HrpS are structurally related to enhancer-binding proteins, but they lack receiver domains and do not appear to require a cognate protein kinase for activity. hrpR and hrpS were shown to be expressed as an operon: a promoter was identified 5' to hrpR, and reverse transcriptase PCR detected the presence of an hrpRS transcript. The hrpR promoter and coding sequence were conserved among P. syringae strains. The coding sequences for hrpR and hrpS were cloned into compatible expression vectors, and their activities were monitored in Escherichia coli transformants carrying an hrpL'-lacZ fusion. HrpS could function as a weak activator of the hrpL promoter, but the activity was only 2.5% of the activity detected when both HrpR and HrpS were expressed in the reporter strain. This finding is consistent with a requirement for both HrpR and HrpS in the activation of the hrpL promoter. By using a yeast two-hybrid assay, an interaction between HrpR and HrpS was detected, suggestive of the formation of a heteromeric complex. Physical interaction of HrpR and HrpS was confirmed by column-binding experiments. The results show that HrpR and HrpS physically interact to regulate the sigma(54)-dependent hrpL promoter in P. syringae strains.