Under pressure: the interplay of hypertension and white matter hyperintensities with cognition in chronic stroke aphasia.

While converging research suggests that increased white matter hyperintensity load is associated with poorer cognition, and the presence of hypertension is associated with increased white matter hyperintensity load, the relationship among hypertension, cognition and white matter hyperintensities is not well understood. We sought to determine the effect of white matter hyperintensity burden on the relationship between hypertension and cognition in individuals with post-stroke aphasia, with the hypothesis that white matter hyperintensity load moderates the relationship between history of hypertension and cognitive function. Health history, Fazekas scores for white matter hyperintensities and Wechsler Adult Intelligence Scale Matrix Reasoning subtest scores for 79 people with aphasia collected as part of the Predicting Outcomes of Language Rehabilitation study at the Center for the Study of Aphasia Recovery at the University of South Carolina and the Medical University of South Carolina were analysed retrospectively. We found that participants with a history of hypertension had increased deep white matter hyperintensity severity (P < 0.001), but not periventricular white matter hyperintensity severity (P = 0.116). Moderation analysis revealed that deep white matter hyperintensity load moderates the relationship between high blood pressure and Wechsler Adult Intelligence Scale scores when controlling for age, education, aphasia severity and lesion volume. The interaction is significant, showing that a history of high blood pressure and severe deep white matter hyperintensities together are associated with poorer Matrix Reasoning scores. The overall model explains 41.85% of the overall variation in Matrix Reasoning score in this group of participants. These findings underscore the importance of considering cardiovascular risk factors in aphasia treatment, specifically hypertension and its relationship to brain health in post-stroke cognitive function.

Regional brain aging: premature aging of the domain general system predicts aphasia severity.

Premature brain aging is associated with poorer cognitive reserve and lower resilience to injury. When there are focal brain lesions, brain regions may age at different rates within the same individual. Therefore, we hypothesize that reduced gray matter volume within specific brain systems commonly associated with language recovery may be important for long-term aphasia severity. Here we show that individuals with stroke aphasia have a premature brain aging in intact regions of the lesioned hemisphere. In left domain-general regions, premature brain aging, gray matter volume, lesion volume and age were all significant predictors of aphasia severity. Increased brain age following a stroke is driven by the lesioned hemisphere. The relationship between brain age in left domain-general regions and aphasia severity suggests that degradation is possible to specific brain regions and isolated aging matters for behavior.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes.

BACKGROUND AND OBJECTIVES: Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties. METHODS: We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time. RESULTS: Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes. DISCUSSION: Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Impact of white matter networks on risk for memory decline following resection versus ablation in temporal lobe epilepsy.

BACKGROUND: With expanding neurosurgical options in epilepsy, it is important to characterise each options' risk for postoperative cognitive decline. Here, we characterise how patients' preoperative white matter (WM) networks relates to postoperative memory changes following different epilepsy surgeries. METHODS: Eighty-nine patients with temporal lobe epilepsy with T1-weighted and diffusion-weighted imaging as well as preoperative and postoperative verbal memory scores (prose recall) underwent either anterior temporal lobectomy (ATL: n=38) or stereotactic laser amygdalohippocampotomy (SLAH; n=51). We computed laterality indices (ie, asymmetry) for volume of the hippocampus and fractional anisotropy (FA) of two deep WM tracts (uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF)). RESULTS: Preoperatively, left-lateralised FA of the ILF was associated with higher prose recall (p<0.01). This pattern was not observed for the UF or hippocampus (ps>0.05). Postoperatively, right-lateralised FA of the UF was associated with less decline following left ATL (p<0.05) but not left SLAH (p>0.05), while right-lateralised hippocampal asymmetry was associated with less decline following both left ATL and SLAH (ps<0.05). After accounting for preoperative memory score, age of onset and hippocampal asymmetry, the association between UF and memory decline in left ATL remained significant (p<0.01). CONCLUSIONS: Asymmetry of the hippocampus is an important predictor of risk for memory decline following both surgeries. However, asymmetry of UF integrity, which is only severed during ATL, is an important predictor of memory decline after ATL only. As surgical procedures and pre-surgical mapping evolve, understanding the role of frontal-temporal WM in memory networks could help to guide more targeted surgical approaches to mitigate cognitive decline.

Improved naming in patients with Broca's aphasia with tDCS.

BACKGROUND: Language impairment (aphasia) is a common neurological deficit after strokes. For individuals with chronic aphasia (beyond 6 months after the stroke), language improvements with speech therapy (ST) are often limited. Transcranial direct current stimulation (tDCS) is a promising approach to complement language recovery but interindividual variability in treatment response is common after tDCS, suggesting a possible relationship between tDCS and type of linguistic impairment (aphasia type). METHODS: This current study is a subgroup analysis of a randomised controlled phase II futility design clinical trial on tDCS in chronic post-stroke aphasia. All participants received ST coupled with tDCS (n=31) vs sham tDCS (n=39). Confrontation naming was tested at baseline, and 1, 4, and 24 weeks post-treatment. RESULTS: Broca's aphasia was associated with maximal adjunctive benefit of tDCS, with an average improvement of 10 additional named items with tDCS+ST compared with ST alone at 4 weeks post-treatment. In comparison, tDCS was not associated with significant benefits for other aphasia types F(1)=4.23, p=0.04. Among participants with Broca's aphasia, preservation of the perilesional posterior inferior temporal cortex was associated with higher treatment benefit (R=0.35, p=0.03). CONCLUSIONS: These results indicate that adjuvant tDCS can enhance ST to treat naming in Broca's aphasia, and this may guide intervention approaches in future studies.

Doxing, political affiliation, and type of information: Effects on suspicion, perceived similarity, and hiring-related judgments.

Researchers have begun to focus on the influence of political affiliation in organizations. In this context, we investigated how doxing (i.e., using social media to post information online with malintent) influences hiring-related decisions. Based on the integration of a political affiliation and state suspicion model, we investigated how a dox containing different types of information (affirming a political party affiliation vs. providing derogatory/negative information about an opposing party) and political party affiliation similarity influenced hiring-related perceptions of job applicants. Given doxing's characteristics, we expanded the "decision space" to include effects about expected organizational image and expected retaliation. In Study 1, we found that the type of information and party similarity influenced suspicion of the applicant and perceived similarity with the applicant, whereas doxing only influenced suspicion. In turn, suspicion and perceived similarity predicted expected task performance and organizational image, and exploratory analyses suggested an interactive effect of these variables. Suspicion also predicted expected retaliation from individuals outside the organization. In Study 2, we confirmed that doxing was related to suspicion as well as the interactive effect of information type and party similarity. We explain that interaction using the notion of symbolic threat. In both studies, the effects of type of information and party similarity were pervasive. Our results support the similarity-attraction paradigm and a model of political affiliation. Expanding relevant theories to include suspicion helps better understand politically related judgments and the additional outcomes of expected organizational image and retaliation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Semantic Categorization of Naming Responses Based on Prearticulatory Electrical Brain Activity.

PURPOSE: Object naming requires visual decoding, conceptualization, semantic categorization, and phonological encoding, all within 400 to 600 ms of stimulus presentation and before a word is spoken. In this study, we sought to predict semantic categories of naming responses based on prearticulatory brain activity recorded with scalp EEG in healthy individuals. METHODS: We assessed 19 healthy individuals who completed a naming task while undergoing EEG. The naming task consisted of 120 drawings of animate/inanimate objects or abstract drawings. We applied a one-dimensional, two-layer, neural network to predict the semantic categories of naming responses based on prearticulatory brain activity. RESULTS: Classifications of animate, inanimate, and abstract responses had an average accuracy of 80%, sensitivity of 72%, and specificity of 87% across participants. Across participants, time points with the highest average weights were between 470 and 490 milliseconds after stimulus presentation, and electrodes with the highest weights were located over the left and right frontal brain areas. CONCLUSIONS: Scalp EEG can be successfully used in predicting naming responses through prearticulatory brain activity. Interparticipant variability in feature weights suggests that individualized models are necessary for highest accuracy. Our findings may inform future applications of EEG in reconstructing speech for individuals with and without speech impairments.

Network coupling and surgical treatment response in temporal lobe epilepsy: A proof-of-concept study.

OBJECTIVE: This proof-of-concept study aimed to examine the overlap between structural and functional activity (coupling) related to surgical response. METHODS: We studied intracranial rest and ictal stereoelectroencephalography (sEEG) recordings from 77 seizures in thirteen participants with temporal lobe epilepsy (TLE) who subsequently underwent resective/laser ablation surgery. We used the stereotactic coordinates of electrodes to construct functional (sEEG electrodes) and structural connectomes (diffusion tensor imaging). A Jaccard index was used to assess the similarity (coupling) between structural and functional connectivity at rest and at various intraictal timepoints. RESULTS: We observed that patients who did not become seizure free after surgery had higher connectome coupling recruitment than responders at rest and during early and mid seizure (and visa versa). SIGNIFICANCE: Structural networks provide a backbone for functional activity in TLE. The association between lack of seizure control after surgery and the strength of synchrony between these networks suggests that surgical intervention aimed to disrupt these networks may be ineffective in those that display strong synchrony. Our results, combined with findings of other groups, suggest a potential mechanism that explains why certain patients benefit from epilepsy surgery and why others do not. This insight has the potential to guide surgical planning (e.g., removal of high coupling nodes) following future research.

White matter hyperintensity load mediates the relationship between age and cognition.

To elucidate the relationship between age and cognitive decline, it is important to consider structural brain changes such as white matter hyperintensities (WMHs), which are common in older age and may affect behavior. Therefore, we aimed to investigate if WMH load is a mediator of the relationship between age and cognitive decline. Healthy participants (N = 166, 20-80 years) completed the Montreal Cognitive Assessment (MoCA). WMHs were manually delineated on FLAIR scans. Mediation analysis was conducted to determine if WMH load mediates the relationship between age and cognition. Older age was associated with worse cognition (p < 0.001), but this was an indirect effect: older participants had more WMHs, and, in turn, increased WMH load was associated with worse MoCA scores. WMH load mediates the relationship between age and cognitive decline. Importantly, this relationship was not moderated by age (i.e., increased WMH severity is associated with poorer MoCA scores irrespective of age). Across all ages, high cholesterol was associated with increased WMH severity.

Neurexin-3 subsynaptic densities are spatially distinct from Neurexin-1 and essential for excitatory synapse nanoscale organization in the hippocampus.

Proteins critical for synaptic transmission are non-uniformly distributed and assembled into regions of high density called subsynaptic densities (SSDs) that transsynaptically align in nanocolumns. Neurexin-1 and neurexin-3 are essential presynaptic adhesion molecules that non-redundantly control NMDAR- and AMPAR-mediated synaptic transmission, respectively, via transsynaptic interactions with distinct postsynaptic ligands. Despite their functional relevance, fundamental questions regarding the nanoscale properties of individual neurexins, their influence on the subsynaptic organization of excitatory synapses and the mechanisms controlling how individual neurexins engage in precise transsynaptic interactions are unknown. Using Double Helix 3D dSTORM and neurexin mouse models, we identify neurexin-3 as a critical presynaptic adhesion molecule that regulates excitatory synapse nano-organization in hippocampus. Furthermore, endogenous neurexin-1 and neurexin-3 form discrete and non-overlapping SSDs that are enriched opposite their postsynaptic ligands. Thus, the nanoscale organization of neurexin-1 and neurexin-3 may explain how individual neurexins signal in parallel to govern different synaptic properties.

Lower socioeconomic status is associated with premature brain aging.

BACKGROUND: Premature age-related brain changes may be influenced by physical health factors. Lower socioeconomic status (SES) is often associated with poorer physical health. In this study, we aimed to investigate the relationship between SES and premature brain aging. METHODS: Brain age was estimated from T1-weighted images using BrainAgeR in 217 participants from the ABC@UofSC Repository. The difference between brain and chronological age (BrainGAP) was calculated. Multiple regression models were used to predict BrainGAP with age, SES, body mass index, diabetes, hypertension, sex, race, and education as predictors. SES was calculated from size-adjusted household income and the cost of living. RESULTS: Fifty-five participants (25.35%) had greater brain age than chronological age (premature brain aging). Multiple regression models revealed that age, sex, and SES were significant predictors of BrainGAP with lower SES associated with greater BrainGAP (premature brain aging). CONCLUSIONS: This study demonstrates that lower SES is an independent contributor to premature brain aging. This may provide additional insight into the mechanisms associated with brain health, cognition, and resilience to neurological injury.

Dynamic network properties of the superior temporal gyrus mediate the impact of brain age gap on chronic aphasia severity.

Brain structure deteriorates with aging and predisposes an individual to more severe language impairments (aphasia) after a stroke. However, the underlying mechanisms of this relation are not well understood. Here we use an approach to model brain network properties outside the stroke lesion, network controllability, to investigate relations among individualized structural brain connections, brain age, and aphasia severity in 93 participants with chronic post-stroke aphasia. Controlling for the stroke lesion size, we observe that lower average controllability of the posterior superior temporal gyrus (STG) mediates the relation between advanced brain aging and aphasia severity. Lower controllability of the left posterior STG signifies that activity in the left posterior STG is less likely to yield a response in other brain regions due to the topological properties of the structural brain networks. These results indicate that advanced brain aging among individuals with post-stroke aphasia is associated with disruption of dynamic properties of a critical language-related area, the STG, which contributes to worse aphasic symptoms. Because brain aging is variable among individuals with aphasia, our results provide further insight into the mechanisms underlying the variance in clinical trajectories in post-stroke aphasia.

Diabetes, brain health, and treatment gains in post-stroke aphasia.

In post-stroke aphasia, language improvements following speech therapy are variable and can only be partially explained by the lesion. Brain tissue integrity beyond the lesion (brain health) may influence language recovery and can be impacted by cardiovascular risk factors, notably diabetes. We examined the impact of diabetes on structural network integrity and language recovery. Seventy-eight participants with chronic post-stroke aphasia underwent six weeks of semantic and phonological language therapy. To quantify structural network integrity, we evaluated the ratio of long-to-short-range white matter fibers within each participant's whole brain connectome, as long-range fibers are more susceptible to vascular injury and have been linked to high level cognitive processing. We found that diabetes moderated the relationship between structural network integrity and naming improvement at 1 month post treatment. For participants without diabetes (n = 59), there was a positive relationship between structural network integrity and naming improvement (t = 2.19, p = 0.032). Among individuals with diabetes (n = 19), there were fewer treatment gains and virtually no association between structural network integrity and naming improvement. Our results indicate that structural network integrity is associated with treatment gains in aphasia for those without diabetes. These results highlight the importance of post-stroke structural white matter architectural integrity in aphasia recovery.

MRI-based deep learning can discriminate between temporal lobe epilepsy, Alzheimer's disease, and healthy controls.

BACKGROUND: Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications of artificial intelligence (AI) assisted technologies. METHOD: We assessed the ability of a convolutional neural network (CNN) algorithm to classify TLE vs. patients with AD vs. healthy controls using T1-weighted magnetic resonance imaging (MRI) scans. We used feature visualization techniques to identify regions the CNN employed to differentiate disease types. RESULTS: We show the following classification results: healthy control accuracy = 81.54% (SD = 1.77%), precision = 0.81 (SD = 0.02), recall = 0.85 (SD = 0.03), and F1-score = 0.83 (SD = 0.02); TLE accuracy = 90.45% (SD = 1.59%), precision = 0.86 (SD = 0.03), recall = 0.86 (SD = 0.04), and F1-score = 0.85 (SD = 0.04); and AD accuracy = 88.52% (SD = 1.27%), precision = 0.64 (SD = 0.05), recall = 0.53 (SD = 0.07), and F1 score = 0.58 (0.05). The high accuracy in identification of TLE was remarkable, considering that only 47% of the cohort had deemed to be lesional based on MRI alone. Model predictions were also considerably better than random permutation classifications (p < 0.01) and were independent of age effects. CONCLUSIONS: AI (CNN deep learning) can classify and distinguish TLE, underscoring its potential utility for future computer-aided radiological assessments of epilepsy, especially for patients who do not exhibit easily identifiable TLE associated MRI features (e.g., hippocampal sclerosis).

In people with temporal lobe epilepsy, seizures start in a particular part of the brain positioned behind the ears called the temporal lobe. It is difficult for a doctor to detect that a person has temporal lobe epilepsy using brain scans. In this study, we developed a computer model that was able to identify people with temporal lobe epilepsy from scans of their brain. This computer model could be used to help doctors identify temporal lobe epilepsy from brain scans in the future.

Advanced Brain Age and Chronic Poststroke Aphasia Severity.

BACKGROUND AND OBJECTIVES: Chronic poststroke language impairment is typically worse in older individuals or those with large stroke lesions. However, there is unexplained variance that likely depends on intact tissue beyond the lesion. Brain age is an emerging concept, which is partially independent from chronologic age. Advanced brain age is associated with cognitive decline in healthy older adults; therefore, we aimed to investigate the relationship with stroke aphasia. We hypothesized that advanced brain age is a significant factor associated with chronic poststroke language impairments, above and beyond chronologic age, and lesion characteristics. METHODS: This cohort study retrospectively evaluated participants from the Predicting Outcomes of Language Rehabilitation in Aphasia clinical trial (NCT03416738), recruited through local advertisement in South Carolina (US). Primary inclusion criteria were left hemisphere stroke and chronic aphasia (≥12 months after stroke). Participants completed baseline behavioral testing including the Western Aphasia Battery-Revised (WAB-R), Philadelphia Naming Test (PNT), Pyramids and Palm Trees Test (PPTT), and Wechsler Adult Intelligence Scale Matrices subtest, before completing 6 weeks of language therapy. The PNT was repeated 1 month after therapy. We leveraged modern neuroimaging techniques to estimate brain age and computed a proportional difference between chronologic age and estimated brain age. Multiple linear regression models were used to evaluate the relationship between proportional brain age difference (PBAD) and behavior. RESULTS: Participants (N = 93, 58 males and 35 females, average age = 61 years) had estimated brain ages ranging from 14 years younger to 23 years older than chronologic age. Advanced brain age predicted performance on semantic tasks (PPTT) and language tasks (WAB-R). For participants with advanced brain aging (n = 47), treatment gains (improvement on the PNT) were independently predicted by PBAD (T = -2.0474, p = 0.0468, 9% of variance explained). DISCUSSION: Through the application of modern neuroimaging techniques, advanced brain aging was associated with aphasia severity and performance on semantic tasks. Notably, therapy outcome scores were also associated with PBAD, albeit only among participants with advanced brain aging. These findings corroborate the importance of brain age as a determinant of poststroke recovery and underscore the importance of personalized health factors in determining recovery trajectories, which should be considered during the planning or implementation of therapeutic interventions.

Longitudinal Progression of White Matter Hyperintensity Severity in Chronic Stroke Aphasia.

Objective: To determine whether longitudinal progression of small vessel disease in chronic stroke survivors is associated with longitudinal worsening of chronic aphasia severity. Design: A longitudinal retrospective study. Severity of white matter hyperintensities (WMHs) as a marker for small vessel disease was assessed on fluid-attenuated inversion recovery (FLAIR) scans using the Fazekas scale, with ratings for deep WMHs (DWMHs) and periventricular WMHs (PVHs). Setting: University research laboratories. Participants: This study includes data from 49 chronic stroke survivors with aphasia (N=49; 15 women, 34 men, age range=32-81 years, >6 months post-stroke, stroke type: [46 ischemic, 3 hemorrhagic], community dwelling). All participants completed the Western Aphasia Battery-Revised (WAB) and had FLAIR scans at 2 timepoints (average years between timepoints: 1.87 years, SD=3.21 years). Interventions: Not applicable. Main Outcome Measures: Change in white matter hyperintensity severity (calculated using the Fazekas scale) and change in aphasia severity (difference in Western Aphasia Battery scores) were calculated between timepoints. Separate stepwise regression models were used to identify predictors of WMH severity change, with lesion volume, age, time between timepoints, body mass index (BMI), and presence of diabetes as independent variables. Additional stepwise regression models investigated predictors of change in aphasia severity, with PVH change, DWMH change, lesion volume, time between timepoints, and age as independent predictors. Results: 22.5% of participants (11/49) had increased WMH severity. Increased BMI was associated with increases in PVH severity (P=.007), whereas the presence of diabetes was associated with increased DWMH severity (P=.002). Twenty-five percent of participants had increased aphasia severity which was significantly associated with increased severity of PVH (P<.001, 16.8% variance explained). Conclusion: Increased small vessel disease burden is associated with contributing to chronic changes in aphasia severity. These findings support the idea that good cardiovascular risk factor control may play an important role in the prevention of long-term worsening of aphasic symptoms.

White matter hyperintensity load is associated with premature brain aging.

BACKGROUND: Brain age is an MRI-derived estimate of brain tissue loss that has a similar pattern to aging-related atrophy. White matter hyperintensities (WMHs) are neuroimaging markers of small vessel disease and may represent subtle signs of brain compromise. We tested the hypothesis that WMHs are independently associated with premature brain age in an original aging cohort. METHODS: Brain age was calculated using machine-learning on whole-brain tissue estimates from T1-weighted images using the BrainAgeR analysis pipeline in 166 healthy adult participants. WMHs were manually delineated on FLAIR images. WMH load was defined as the cumulative volume of WMHs. A positive difference between estimated brain age and chronological age (BrainGAP) was used as a measure of premature brain aging. Then, partial Pearson correlations between BrainGAP and volume of WMHs were calculated (accounting for chronological age). RESULTS: Brain and chronological age were strongly correlated (r(163)=0.932, p<0.001). There was significant negative correlation between BrainGAP scores and chronological age (r(163)=-0.244, p<0.001) indicating that younger participants had higher BrainGAP (premature brain aging). Chronological age also showed a positive correlation with WMH load (r(163)=0.506, p<0.001) indicating older participants had increased WMH load. Controlling for chronological age, there was a statistically significant relationship between premature brain aging and WMHs load (r(163)=0.216, p=0.003). Each additional year in brain age beyond chronological age corresponded to an additional 1.1mm3 in WMH load. CONCLUSIONS: WMHs are an independent factor associated with premature brain aging. This finding underscores the impact of white matter disease on global brain integrity and progressive age-like brain atrophy.

Outcome Quality After Colorectal Cancer Resection in Certified Colorectal Cancer Centers­Patient-Reported and Short-Term Clinical Outcomes.

BACKGROUND: In this observational study, patient-reported outcomes and short-term clinical outcome parameters in patients with colorectal cancer were studied 12 months after the start of treatment. Outcomes were also compared across German Certified Colorectal Cancer Centres. METHODS: Data were collected from 4239 patients with colorectal cancer who had undergone elective tumor resection in one of 102 colorectal cancer centers and had responded to a quality-of-life questionnaire before treatment (EORTC QLQ-C30 and -CR29). 3142 (74.1%) of these patients completed a post-treatment questionnaire 12 months later. Correlation analyses were calculated and case-mix adjusted comparisons across centers were made for selected patient-reported outcomes, anastomotic insufficiency, and 30-day-mortality. RESULTS: At 12 months, mild improvements were seen in mean quality-of-life scores (66 vs. 62 points), constipation (16 vs. 19), and abdominal pain (15 vs. 17). Worsening was seen in physical function (75 vs. 82) and pain (22 vs. 19). Better patient-reported outcomes at 12 months were associated with better scores before treatment. Better results in at least three of the five scores were associated with male sex, higher educational level, higher age, and private health insurance. Major worsening of fecal incontinence was seen among patients with rectal cancer without a stoma. The largest differences across centers were found with respect to physical function. Anastomotic insufficiency was found in 4.3% of colon cancer patients and 8.2% of rectal cancer patients. 1.9% of patients died within 30 days after their resection. CONCLUSION: Clinicians can use these findings to identify patients at higher risk for poorer patient-reported outcomes. The differences among cancer centers that were found imply that measures for quality improvement would be desirable.

Neural network bases of thematic semantic processing in language production.

Semantic processing is a central component of language and cognition. The anterior temporal lobe is postulated to be a key hub for semantic processing, but the posterior temporoparietal cortex is also involved in thematic associations during language. It is possible that these regions act in concert and depend on an anteroposterior network linking the temporal pole with posterior structures to support thematic semantic processing during language production. We employed connectome-based lesion-symptom mapping to examine the causal relationship between lesioned white matter pathways and thematic processing language deficits among individuals with post-stroke aphasia. Seventy-nine adults with chronic aphasia completed the Philadelphia Naming Test, and semantic errors were coded as either thematic or taxonomic to control for taxonomic errors. Controlling for nonverbal conceptual-semantic knowledge as measured by the Pyramids and Palm Trees Test, lesion size, and the taxonomic error rate, thematic error rate was associated with loss of white matter connections from the temporal pole traversing in peri-Sylvian regions to the posterior cingulate and the insula. These findings support the existence of a distributed network underlying thematic relationship processing in language as opposed to discrete cortical areas.

Results of the Cologne Corona surveillance (CoCoS) study - a prospective population-based cohort study: incidence data and potential underestimation of new SARS-CoV-2 adult infections by health authorities.

BACKGROUND: Current incidence estimates of SARS-CoV-2 in Germany rely to a large extent on case notifications. However, the large number of mild or asymptomatic infections is likely to result in underestimation. Population-based studies can provide valid estimates of the SARS-CoV-2 incidence and thus support health authorities to monitor the epidemiological situation and to initiate, maintain, strengthen or relax effective countermeasures. METHODS: This study was conducted in Cologne, Germany. Six-thousand randomly drawn Cologne residents, 18 years of age or older, were contacted by mail in March 2021. Study envelopes contained a kit for self-administered saliva sample and access details to a questionnaire on sociodemographic characteristics, previous positive SARS-CoV-2 RT-qPCR and completed COVID-19 vaccinations. Participants were again invited for a second round in June 2021, while those who declined participation were replaced by additional randomly drawn Cologne residents in order to reach a total of 6000 potential participants again. The saliva samples were sent to the laboratory by mail and tested for SARS-CoV-2 using RT-qPCR. The incidence estimates were adjusted for sensitivity and specificity of the test procedure and compared with the official numbers of new SARS-CoV-2 cases in the adult Cologne population. RESULTS: The first surveillance round in March 2021 (response rate: 34.08%, N = 2045) showed a SARS-CoV-2 seven-day incidence of 85 cases per 100,000 adult Cologne residents (95% CI: 9 to 319). In the same period, the officially registered cases were 125 per 100,000. The second surveillance round in June 2021 (response rate: 36.53%, N = 2192) showed a seven-day incidence of 27 per 100,000 adult Cologne residents (95% CI: 1 to 142), while the official figures for newly registered SARS-CoV-2 cases in the same period were 15 per 100,000. CONCLUSIONS: The incidence estimates do not indicate relevant underestimation of new SARS-CoV-2 infections based on case notification. Regular use of the surveillance method developed here may nevertheless complement the efforts of the health authorities to assess the epidemiological situation. TRIAL REGISTRATION: DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046 , Registered on 25 February 2021.