Inverted perovskite solar cells (PSCs) often suffer from inefficient electron extraction due to the intrinsically p-type nature of the perovskite surface at the electron transport layer interface. Here, we report a near-surface sulfidation strategy using dibutyl sulfide (DBS) to induce a surface p-to-n transition, which creates a near-surface electric field that facilitates electron extraction and suppresses interfacial recombination. Simultaneously, the formation of Pb-S coordination bonds passivates undercoordinated Pb2+ defects, reducing nonradiative recombination losses. As a result, DBS-treated inverted PSCs achieve a champion power conversion efficiency of 26.28% with a high open-circuit voltage of 1.191 V. The treated devices also exhibit enhanced thermal stability, retaining 91% of their initial efficiency after more than 700 h of aging at 85 °C in a N2 atmosphere. This work presents a simple yet effective surface engineering approach that simultaneously enhances both the efficiency and stability of inverted PSCs.

This work establishes a facile and integrated strategy combining deep eutectic solvent (DES) selective extraction and in situ polymerization to upcycle low-value coal tar phenolics into high-performance defective porous carbon for zinc-ion hybrid capacitors (ZIHCs). Benefiting from strong hydrogen-bonding interaction, aldehyde-functionalized DES achieves efficient separation of phenolic components from coal tar with an extraction efficiency up to 94.73%. Eliminating tedious back-extraction procedures, the phenolic-enriched system realizes pH-regulated in situ polymerization to fabricate three types of phenolic resin precursors with distinct molecular architectures. The three-dimensional, oxygen-rich precursor formed under alkaline conditions induces steric hindrance that suppresses aromatic stacking during carbonization, yielding highly defective porous carbon. Combined with rational activation treatment, all derived carbon materials exhibit well-developed pore structures and favorable capacitive performance. Notably, the extraction phase is innovatively reused to fabricate a highly conductive gel electrolyte. The assembled ZIHC using prepared porous carbon and gel electrolyte achieves a favorable specific capacity of 257.9 mAh g-1, a high energy density of 186.9 Wh kg-1, and ultra-long cycling durability. This study clarifies the intrinsic correlation between precursor microstructure, carbon defect configuration and electrochemical energy storage behavior, and provides a new strategy for high-value sustainable utilization of coal tar toward advanced energy storage devices.

The prevalence of back pain in humans has been extensively reported, but in dogs it is unknown. In horses, research on the prevalence of back pain exists, but with reports ranging from 1% to 94%, indicating a data deficiency.

Oral diseases remain among the most prevalent chronic conditions worldwide, yet their prevention and long-term management depend heavily on patient understanding of self-care, maintenance protocols, and procedural risks. Existing educational programs have not solved this problem because most individuals do not understand dental health, and communication with patients remains poor, which results in poor treatment outcomes. The teach-back method functions as an evidence-based communication tool that helps staff members confirm that patients have grasped essential information, but dental practitioners use it inconsistently because it requires manual work and produces no measurable biological results. This review presents artificial intelligence (AI)-augmented teach-back as a communication system that unites dental evidence with healthcare field evidence to create a scalable system that maintains equity and enables verification. The review uses conceptual synthesis based on implementation science together with digital health and clinical communication research to study teach-back applications in pediatric, preventive, periodontal, surgical, geriatric, tele-dental, and public-health dentistry, which face three main challenges: standardization, workflow burden, and outcome measurement. Advances in natural language processing, speech recognition, semantic understanding scoring, explainable AI (XAI), and risk-adaptive communication systems have enabled teach-back to evolve from its original form as a recall-based educational method into a clinical process that can be audited and produces long-term results. This review uses three established frameworks together with the SALIENT AI-specific governance model to evaluate organisation readiness for implementation, their ethical safeguards, and their methods for achieving equity. The system provides three main advantages, including its ability to combine information from various fields, its design to match actual operational procedures, and its direct connection between communication verification methods and biological measurement results. This study depends on indirect evidence that comes from non-dental environments but does not include future dental research studies. The review presents communication as a clinical risk that can be modified and demonstrates how AI-augmented teach-back functions as a ready-to-use system for dental care improvement through better patient adherence and enhanced safety and equity distribution.

Rituximab, a chimeric anti-CD20 monoclonal antibody, is widely used to treat autoimmune diseases and hematologic malignancies through B-cell depletion, yet paradoxical autoimmune phenomena, including drug-induced lupus erythematosus, have been increasingly recognized. While paradoxical autoimmune phenomena following rituximab therapy have been reported, drug-induced subacute cutaneous lupus erythematosus (DI-SCLE) represents an exceedingly rare complication. This case reports rituximab-induced SCLE in a patient with Sjögren's disease and demonstrates the dual therapeutic efficacy of anifrolumab in managing both drug-induced cutaneous lupus and interferon-driven systemic manifestations. A 69-year-old woman with established primary Sjögren's disease and cryoglobulinemic vasculitis developed biopsy-proven subacute cutaneous lupus erythematosus with clinical onset approximately 4 months following rituximab administration, with histopathological confirmation at Month 9. The patient presented with characteristic erythematous lesions on the trunk and back, which subsequently recurred with extension to the face and décolleté; histopathological examination revealed interface dermatitis and a positive lupus band test on direct immunofluorescence. Treatment with anifrolumab (300 mg intravenously every 4 weeks) resulted in complete resolution of rituximab-induced SCLE. Subsequent addition of low-dose mycophenolate mofetil (1,000 mg daily) achieved complete remission of cryoglobulinemic vasculitis, with sustained disease control maintained on this anifrolumab-based regimen. Clinicians should maintain vigilance for paradoxical cutaneous reactions following B-cell-depleting therapies, particularly in patients with underlying Sjögren's disease and anti-Ro/SSA positivity.

Droplet microfluidics with droplet generation frequencies of several hundred hertz and droplet volumes below 1 nL has previously been reported for biphasic chemical sensing based on oil sensors. However, tracking fluorescence from these rapidly moving subnanoliter droplets typically requires highly sophisticated optical instrumentation, such as laser-scanning confocal microscopy. In this work, we implement oil-based chemical sensing in segmented-flow microfluidics with operating frequencies below 20 Hz and segment volumes of tens to hundreds of nanoliters. The lower segment generation frequency and larger segment size enable straightforward interrogation using a compact custom-built optical detector consisting of a laser excitation source and a photon counter. Commercial plastic tee assemblies and perfluorinated tubing are employed in place of PDMS microchannels to minimize channel swelling as well as chemical adsorption and absorption. The self-contained sensing platform is demonstrated for biphasic detection of potassium ions, albumin, and hydrogen peroxide based on mechanisms including analyte-induced deprotonation of a hydrophobic pH indicator, analyte-induced back extraction of a fluorescent dye, and reaction of the analyte with a fluorescent probe. The system is compatible with oil sensors containing optical reporters over a wide concentration range from micromolar to near-millimolar levels. Using potassium ion sensing as a model system, we further demonstrate plasma analysis and real-time tracking of stepwise concentration changes in continuously aspirated samples. This low-frequency segmented-flow microfluidic sensing platform combined with a simple optical detector paves the way for bedside chemical monitoring in biological fluids.

Animal studies remain indispensable for research on Alzheimer's disease (AD), vascular cognitive impairment, and other dementia-relevant mechanisms. Their value, however, is not that they reproduce human late-life dementia in miniature. A mouse line, vascular manipulation, or mixed-pathology preparation can make one aspect of the problem experimentally visible while not capturing the long preclinical course, clinical heterogeneity, and everyday functional consequences that define the human syndrome. This review therefore treats animal models as instruments for bounded inference. Drawing on translational, mechanistic, and methodological literature, we ask which biological question is posed, which outcome can legitimately answer it, and where the claim should be drawn back. The Question-Model-Outcome framework is developed around five recurrent problems: the loose relation between lesion burden and functional severity; vascular influences on proteinopathy and network injury; stage-dependent immune and glial responses; the narrow construct validity of many behavioral assays; and the interpretation of reported improvement after intervention. We argue that translational value arises when model biology, disease stage, and outcome level are aligned. In that role, animal studies can sharpen mechanistic reasoning and discipline clinical extrapolation without being treated as generic substitutes for human AD-related dementia.

Whether Daylight Saving Time (DST) transitions increase traffic crashes remains a contested policy question, with prior studies reporting 5%-7% increases in fatal crashes over the week following spring-forward but lacking a non-DST control group to isolate the clock-shift effect from seasonal confounding. We address this gap using a difference-in-differences (DiD) design with jurisdictions that do not observe DST as controls. An illustrative city-level analysis uses police-reported crash data from seven U.S. cities (2012-2025), including Tempe, Arizona - which does not observe DST - as a control; this analysis is reported in Appendix A. Our primary analysis uses the Fatality Analysis Reporting System (FARS), covering 375,658 fatal crashes across all 50 U.S. states and the District of Columbia from 2012 to 2022, with Arizona and Hawaii as non-DST controls, in a ±14-day window around each transition. In the illustrative city comparison, adding a non-DST city changes the positive uncontrolled estimate to a near-zero coefficient, although failed diagnostics preclude city-level causal inference. In the primary FARS DiD, for which pre-trend tests do not reject the null of no differential trends, the estimate for overall fatal-crash counts is also null (＋0.2%, p=0.954, ±14-day window). However, morning (6-10 AM) fatal crashes increase by ＋25.9% (p=0.007) in the 6:00-9:59 AM slot averaged over the ±14-day spring-forward window (post-transition days 0-14 vs. pre-transition days -14 to -1)-an effect that strengthens to ＋26.8% (p=0.002) once month-of-year fixed effects and day-of-week-by-DST interactions are added, remains similar when scaled by annual state-level vehicle-miles-traveled (＋22.8%, p=0.016), and is robust to bandwidth as narrow as ±3 days (＋45.8%, p=0.003) and to the exclusion of either non-DST control state. All FARS-based estimates pertain to fatal-crash counts, not crash risk per trip; annual VMT scaling cannot absorb short-run or intraday changes in traffic exposure. The post-transition pattern is not readily attributable to acute sleep deprivation alone and instead points to potentially interacting sleep, circadian, ambient-light, and traffic-exposure channels that this design cannot separately identify. The fall-back effect on total fatal-crash counts likewise vanishes with controls, a pattern consistent with seasonal confounding rather than a clock-shift effect. These findings suggest that prior uncontrolled comparisons may overstate DST's overall crash effect, while underscoring a targeted morning fatal-crash-count increase that merits policy attention.